Fault determination method, device and electronic equipment for transformer

Abstract

The present invention discloses a method, apparatus and electronic device for determining a fault of a transformer. Wherein, the method includes: collecting visible light signals inside the transformer cavity; determining the signal wavelength of the visible light signals and the signal intensity corresponding to the signal wavelength; determining a wavelength concentration value of the visible light signals according to the signal wavelength and the signal intensity corresponding to the signal wavelength; in the case where the wavelength concentration value does not belong to a predetermined wavelength interval, determining a first wavelength distance index of the wavelength concentration value from a predetermined wavelength value; in the case where the first wavelength distance index is less than a wavelength predetermined index, collecting audible signals inside the transformer cavity; and determining the fault type of the fault inside the transformer cavity according to the audible signals. The present invention solves the technical problem in the related art that it is difficult to accurately determine the fault inside the transformer cavity.

Description

Technical Field

[0001] The present invention relates to the field of transformers, and in particular, to a method, device, and electronic device for determining faults of a transformer. Background Art

[0002] As a core main device in the power system, the oil-immersed power transformer is a key node in the electric energy transmission channel, and its safe and stable operation is crucial for the reliability of the power system and the construction of the energy Internet. Therefore, it is of great significance to timely detect internal faults and arrange maintenance in a timely manner to improve the safe operation ability of the transmission and transformation power grid. Using the methods provided in the related technologies, it is difficult to accurately determine the faults in the transformer cavity.

[0003] In view of the above problems, no effective solution has been proposed yet. Summary of the Invention

[0004] Embodiments of the present invention provide a method, device, and electronic device for determining faults of a transformer, so as to at least solve the technical problem that it is difficult to accurately determine the faults in the transformer cavity in the related technologies.

[0005] According to an aspect of an embodiment of the present invention, a method for determining faults of a transformer is provided, including: collecting visible light signals in the transformer cavity; determining the signal wavelength of the visible light signals and the signal intensity corresponding to the signal wavelength; determining a wavelength concentration value of the visible light signals according to the signal wavelength and the signal intensity corresponding to the signal wavelength; in the case where the wavelength concentration value does not belong to a predetermined wavelength interval, determining a first wavelength distance index of the wavelength concentration value from a predetermined wavelength value; in the case where the first wavelength distance index is less than a wavelength predetermined index, collecting audible signals in the transformer cavity; determining the fault type of the fault in the transformer cavity according to the audible signals.

[0006] Optionally, determining the fault type of the fault in the transformer cavity according to the audible signals includes: determining the signal frequency of the audible signals and the signal amplitude corresponding to the signal frequency; determining a frequency concentration value of the audible signals according to the signal frequency and the signal amplitude corresponding to the signal frequency; determining the fault type of the fault in the transformer cavity according to the frequency concentration value.

[0007] Optionally, determining the fault type of the fault in the transformer cavity according to the frequency concentration value includes: determining a first frequency distance index between the frequency concentration value and a first predetermined frequency value, and determining a second frequency distance index between the frequency concentration value and a second predetermined frequency value, where the first predetermined frequency value is a frequency value corresponding to an uneven field discharge fault, and the second predetermined frequency value is a frequency value corresponding to a uniform field discharge fault; determining the fault type of the fault in the transformer cavity according to the first frequency distance index and the second frequency distance index.

[0008] Optionally, determining the fault type of the fault in the transformer cavity according to the frequency concentration value includes: when the first frequency distance index is less than a frequency predetermined index and the second frequency distance index is greater than or equal to the frequency predetermined index, determining that the fault type is the uneven field discharge fault, and / or, when the first frequency distance index is greater than or equal to the frequency predetermined index and the second frequency distance index is less than the frequency predetermined index, determining that the fault type is the uniform field discharge fault.

[0009] Optionally, after determining the wavelength concentration value of the visible light signal according to the signal wavelength and the signal intensity corresponding to the signal wavelength, further includes: when the wavelength concentration value belongs to the predetermined wavelength interval, determining that the fault type is a surface discharge fault.

[0010] Optionally, when the wavelength concentration value does not belong to the predetermined wavelength interval, after determining a first wavelength distance index between the wavelength concentration value and a predetermined wavelength value, further includes: when the first wavelength distance index is greater than or equal to a wavelength predetermined index, determining a second wavelength distance index between the wavelength concentration value and the predetermined wavelength interval; when the second wavelength distance index is less than the wavelength predetermined index, determining the frequency concentration value of the audible signal; when a third distance index between the frequency concentration value and a third predetermined frequency value is less than the frequency predetermined index, determining that the fault type is a surface discharge fault.

[0011] Optionally, after determining the fault type of the fault in the transformer cavity according to the audible signal, further includes: determining a fault handling method corresponding to the fault type; sending a fault handling instruction to a terminal device corresponding to the fault handling method, where the fault handling instruction carries the fault handling method.

[0012] According to one aspect of an embodiment of the present invention, there is provided a fault determination device for a transformer, including: a first acquisition module configured to acquire visible light signals inside the transformer cavity; a first determination module configured to determine the signal wavelength of the visible light signals and the signal intensity corresponding to the signal wavelength; a second determination module configured to determine a wavelength concentration value of the visible light signals based on the signal wavelength and the signal intensity corresponding to the signal wavelength; a third determination module configured to determine a first wavelength distance index of the wavelength concentration value from a predetermined wavelength value when the wavelength concentration value does not belong to a predetermined wavelength interval; a second acquisition module configured to acquire audible signals inside the transformer cavity when the first wavelength distance index is less than a wavelength predetermined index; a fourth determination module configured to determine a fault type of a fault inside the transformer cavity based on the audible signals.

[0013] According to one aspect of an embodiment of the present invention, there is provided an electronic device, including: a processor; a memory for storing requests executable by the processor; wherein the processor is configured to execute the requests to implement the fault determination method for a transformer as described in any one of the above.

[0014] According to one aspect of an embodiment of the present invention, there is provided a computer-readable storage medium, including: when requests in the computer-readable storage medium are executed by a processor of an electronic device, enabling the electronic device to execute the fault determination method for a transformer as described in any one of the above.

[0015] In an embodiment of the present invention, visible light signals inside the transformer cavity are collected, the signal wavelengths of the visible light signals are determined, as well as the signal intensities corresponding to the signal wavelengths. Based on the signal wavelengths and the signal intensities corresponding to the signal wavelengths, a wavelength concentration value of the visible light signals is determined. In the case where the wavelength concentration value does not belong to a predetermined wavelength interval, a first wavelength distance index of the wavelength concentration value from a predetermined wavelength value is determined. In the case where the first wavelength distance index is less than a wavelength predetermined index, audible signals inside the transformer cavity are collected, and based on the audible signals, the fault type of the fault inside the transformer cavity is determined. Since the fault type of the fault inside the transformer cavity can be determined based on the audible signals, by analyzing the audible signals inside the transformer cavity, potential fault conditions can be detected early. Different types of faults usually produce specific sound characteristics, and sound diagnosis can be used to detect faults at the early stage of fault development, avoiding further deterioration of the faults and causing greater damage. By timely identifying faults through sound diagnosis technology and taking corresponding maintenance measures, potential electrical accidents and outages can be avoided, and the service life of the transformer can be extended. Moreover, by determining the wavelength concentration value of the visible light signals, not only can the spectral characteristics of the signals be deeply understood, which helps to understand the characteristics and change trends of the signals and provides a basis for analyzing and interpreting the behavior of the visible light signals, but also abnormal wavelength or frequency components that may exist in the signals can be detected, so as to detect potential fault conditions early, perform accurate fault diagnosis, and take corresponding repair and restoration measures, thus solving the technical problem in the related art that it is difficult to accurately determine the faults inside the transformer cavity. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation on the present invention. In the drawings:

[0017] Figure 1 is a flowchart of a method for determining faults of a transformer according to an embodiment of the present invention;

[0018] Figure 2 is a structural block diagram of a device for determining faults of a transformer according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0020] It should be noted that the terms "first", "second", etc. in the description, claims and above-mentioned drawings of the present invention are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present invention described here can be implemented in an order different from those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0021] Embodiment 1

[0022] According to an embodiment of the present invention, an embodiment of a method for determining a fault of a transformer is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order from here.

[0023] Figure 1 is a flowchart of a method for determining a fault of a transformer according to an embodiment of the present invention, as Figure 1 shown, the method includes the following steps:

[0024] Step S102, collect visible light signals inside the transformer cavity;

[0025] In step S102 provided in the present application, the above-mentioned visible light signals inside the transformer cavity may be that there may be a discharge phenomenon inside the transformer cavity, such as arc, electric spark or corona discharge, and visible light signals related to the discharge phenomenon usually occur. If there are pollutants or gas leaks, and these substances burn, visible light signals may be generated.

[0026] It should be noted that a selected optical sensor can be placed at an appropriate position inside the transformer cavity, and the acquisition system can be started to record the visible light signals inside the transformer cavity. After the acquisition is completed, the recorded optical signal data can be analyzed and processed. By collecting the visible light signals inside the transformer cavity, on the one hand, it can help diagnose and detect potential faults or abnormal conditions, so as to take preventive and maintenance measures in advance, ensure the reliability and safety of the system operation, and can also more accurately and quickly determine the location of the fault, saving the time and cost of troubleshooting.

[0027] Step S104, determine the signal wavelength of the visible light signal and the signal intensity corresponding to the signal wavelength;

[0028] In step S104 provided in this application, the wavelength of the above visible light signal is within the range of visible light in the electromagnetic spectrum. The signal intensity can be described by light intensity, which is not limited herein and can be selected according to specific scenarios and applications.

[0029] It should be noted that there may be multiple sources of visible light signals with different wavelengths and intensities in the transformer cavity, and the specific situation may vary depending on the specific transformer type, operating conditions, and existing fault conditions. Therefore, in order to accurately determine the signal wavelength and the corresponding signal intensity, appropriate optical sensors or spectral analysis instruments need to be used, and detailed tests and analyses need to be carried out. By monitoring the wavelength and intensity of the visible light signal, possible faults or abnormal conditions inside the transformer can be detected to avoid equipment failures or accidents, and to a certain extent, the risk of accidents and losses can be reduced.

[0030] Step S106: Determine the wavelength concentration value of the visible light signal based on the signal wavelength and the signal intensity corresponding to the signal wavelength.

[0031] In step S106 provided in this application, according to the wavelength range of the visible light signal and the corresponding light intensity situation, the wavelength concentration value of the visible light signal can be determined. The wavelength concentration value may refer to the value corresponding to the wavelength with the highest signal intensity, or the center of gravity of the signal intensity distribution, and may vary depending on specific applications and environments. Therefore, the actual wavelength concentration value may need to be accurately calculated based on specific spectral measurement data, which is not limited herein.

[0032] It should be noted that by determining the wavelength concentration value of the visible light signal, not only can the spectral characteristics of the signal be deeply understood, which helps to understand the characteristics and change trends of the signal and provides a basis for analyzing and interpreting the behavior of the visible light signal, but also abnormal wavelength or frequency components that may exist in the signal can be detected, so as to discover potential fault conditions early, conduct accurate fault diagnosis, and take corresponding maintenance and repair measures.

[0033] Step S108: When the wavelength concentration value does not belong to the predetermined wavelength interval, determine the first wavelength distance index of the wavelength concentration value from the predetermined wavelength value.

[0034] In step S108 provided in this application, first determine the predetermined wavelength interval, that is, the wavelength range in which the wavelength concentration value is required to be located. Assume that the predetermined wavelength interval is [a, b], where a and b are the lower and upper limits of the predetermined wavelength range. Through spectral analysis or measurement data, determine the actual wavelength concentration value and calculate the first wavelength distance index of the wavelength concentration value from the predetermined wavelength value. The larger the value of the first wavelength distance index, the farther the actual wavelength concentration value is from the predetermined wavelength interval.

[0035] It should be noted that by calculating the exponent, the distance between the actual wavelength concentration value and the predetermined wavelength value can be evaluated. This not only helps to understand the difference between the actual wavelength concentration and the predetermined wavelength value, but also enables the rapid detection and location of fault points in optical devices, sensors or optical fibers. For example, when the exponent exceeds a certain threshold, an alarm or further troubleshooting can be triggered to improve the reliability and stability of the system.

[0036] Step S110: When the first wavelength distance exponent is less than the wavelength predetermined exponent, collect the audible sound signal in the transformer cavity.

[0037] In step S110 provided in this application, when the first wavelength distance exponent is less than the wavelength predetermined exponent, the sound collection device can be activated to record the sound signal in the transformer cavity. That is, based on the magnitude relationship of the exponents, it can be inferred that there may be mechanical vibrations or sound waves in the transformer cavity that are relatively close to the predetermined wavelength.

[0038] It should be noted that by collecting the audible sound signal in the transformer cavity, on the one hand, abnormal sounds in the transformer cavity can be detected, which helps to take preventive measures for repair and maintenance in advance to avoid more serious faults and damages. On the other hand, a health status baseline of the transformer can be established, which helps to monitor the health status of the transformer in real time and take necessary repair and maintenance measures in a timely manner to ensure the safe and reliable operation of the transformer.

[0039] Step S112: Determine the fault type of the fault in the transformer cavity based on the audible sound signal.

[0040] In step S112 provided in this application, based on the audible sound signal collected in the previous steps, the analysis of the sound characteristics and the fault sound pattern is carried out to further determine the fault type of the fault in the transformer cavity. In this step, the fault type can be surface discharge, extremely non-uniform field discharge, or uniform field discharge. The fault type is not limited here and can be determined according to specific scenarios and applications.

[0041] It should be noted that by analyzing the audible sound signal in the transformer cavity, potential fault situations can be detected early. Different types of faults usually produce specific sound characteristics. Using sound diagnosis, faults can be detected at the early stage of fault development to avoid further deterioration of the faults and greater damages. By timely identifying faults through sound diagnosis technology and taking corresponding maintenance measures, potential electrical accidents and shutdowns can be avoided, and the service life of the transformer can be extended.

[0042] Through the above steps S102 - S112, the visible light signal in the transformer cavity is collected, the signal wavelength of the visible light signal is determined, and the signal intensity corresponding to the signal wavelength is determined. Based on the signal wavelength and the signal intensity corresponding to the signal wavelength, the wavelength concentration value of the visible light signal is determined. When the wavelength concentration value does not belong to the predetermined wavelength interval, the first wavelength distance index of the wavelength concentration value from the predetermined wavelength value is determined. When the first wavelength distance index is less than the wavelength predetermined index, the audible signal in the transformer cavity is collected. Based on the audible signal, the fault type of the fault in the transformer cavity is determined. Since the fault type of the fault in the transformer cavity can be determined based on the audible signal, by analyzing the audible signal in the transformer cavity, potential fault situations can be detected early. Different types of faults usually produce specific sound characteristics. Using sound diagnosis, faults can be detected at the early stage of fault development, avoiding further deterioration of the faults and causing greater damage. By timely identifying faults through sound diagnosis technology and taking corresponding maintenance measures, potential electrical accidents and outages can be avoided, and the service life of the transformer can be extended. Moreover, by determining the wavelength concentration value of the visible light signal, not only can the spectral characteristics of the signal be deeply understood, which helps to understand the characteristics and change trends of the signal, providing a basis for analyzing and interpreting the behavior of the visible light signal, but also abnormal wavelength or frequency components that may exist in the signal can be detected, so as to detect potential fault situations early, perform accurate fault diagnosis, and take corresponding repair and restoration measures, thus solving the technical problem in the related technology that it is difficult to accurately determine the faults in the transformer cavity.

[0043] As an optional embodiment, determining the fault type of the fault in the transformer cavity based on the audible signal includes: determining the signal frequency of the audible signal and the signal amplitude corresponding to the signal frequency; determining the frequency concentration value of the audible signal based on the signal frequency and the signal amplitude corresponding to the signal frequency; and determining the fault type of the fault in the transformer cavity based on the frequency concentration value.

[0044] In this embodiment, the audible signal is obtained based on the signal acquisition device, and signal processing and analysis are performed to determine the range of the signal frequency and the corresponding signal amplitude. Then, according to the determined signal frequency and the signal amplitude corresponding to the signal frequency, the peak or concentrated area with the highest frequency amplitude is found, that is, the frequency concentration value. Further, the obtained frequency concentration value is compared and matched with the sound frequency characteristics of known fault types to determine the fault type of the fault in the transformer cavity.

[0045] It should be noted that by determining the signal frequency and signal amplitude of the audible sound signal, the characteristics in the fault signal can be identified and extracted, enabling the fault signal to be distinguished from the background noise. To a certain extent, this helps to determine the true fault signal and reduce the possibility of misjudgment. Moreover, by determining the frequency concentration value of the audible sound signal, it is possible to assist in locating the frequency range of the fault signal, so as to provide preliminary fault type location information.

[0046] It should also be noted that by comparing and matching the frequency concentration value with the sound frequency characteristics of known fault types, not only can the possible fault types be preliminarily judged, but it also helps to improve the accuracy and efficiency of fault diagnosis, guide the maintenance and preventive maintenance work, and enhance the safety and reliability of the transformer system.

[0047] As an optional embodiment, based on the frequency concentration value, determine the fault type of the fault in the transformer cavity, including: determining the first frequency distance index between the frequency concentration value and the first predetermined frequency value, and determining the second frequency distance index between the frequency concentration value and the second predetermined frequency value, where the first predetermined frequency value is the frequency value corresponding to the non-uniform field discharge fault, and the second predetermined frequency value is the frequency value corresponding to the uniform field discharge fault; determine the fault type of the fault in the transformer cavity according to the first frequency distance index and the second frequency distance index.

[0048] In this embodiment, the first predetermined frequency value can be the frequency value corresponding to the non-uniform field discharge fault, the second predetermined frequency value can be the frequency value corresponding to the uniform field discharge fault, and the frequency concentration value is the frequency concentration value of the audible sound signal determined according to the previous steps.

[0049] For the above steps, the first frequency distance index can be determined by calculating the distance between the frequency concentration value and the first predetermined frequency value, and the second frequency distance index can be determined by the distance between the frequency concentration value and the second predetermined frequency value. Then, according to the magnitude relationship between the first frequency distance index and the second frequency distance index determined above, the fault type of the fault in the transformer cavity can be preliminarily determined.

[0050] It should be noted that by using the comparison of the first frequency distance index and the second frequency distance index, the fault type of the fault in the transformer cavity can be quickly and preliminarily judged, which helps to quickly understand the fault characteristics during the fault diagnosis process and guide the subsequent maintenance work. That is, based on the first frequency distance index and the second frequency distance index to determine the fault type of the fault in the transformer cavity can improve the speed and accuracy of fault diagnosis, guide the fault location and repair work, and enhance the safety and reliability of the transformer system.

[0051] As an alternative embodiment, determining the fault type of a fault within the transformer cavity based on the frequency concentration value includes: when the first frequency distance index is less than the frequency predetermined index and the second frequency distance index is greater than or equal to the frequency predetermined index, determining that the fault type is an uneven field discharge fault, and / or, when the first frequency distance index is greater than or equal to the frequency predetermined index and the second frequency distance index is less than the frequency predetermined index, determining that the fault type is a uniform field discharge fault.

[0052] In this embodiment, when the second frequency distance index is greater than or equal to the frequency predetermined index, it can be determined that the fault type is an uneven field discharge fault. In this case, the frequency predetermined index can indicate that the frequency concentration value is closer to the predetermined frequency corresponding to the uneven field discharge fault. And when the first frequency distance index is greater than or equal to the frequency predetermined index and the second frequency distance index is less than the frequency predetermined index, it can be determined that the fault type is a uniform field discharge fault. In this case, the frequency predetermined index can indicate that the frequency concentration value is closer to the predetermined frequency corresponding to the uniform field discharge fault.

[0053] It should be noted that by analyzing and comparing the frequency concentration value, the fault type can be preliminarily determined as an uneven field discharge fault or a uniform field discharge fault. To a certain extent, this not only helps to accurately locate the fault, ensure the adoption of correct fault handling methods during the maintenance process, but also improves the efficiency of fault detection.

[0054] As an alternative embodiment, after determining the wavelength concentration value of the visible light signal based on the signal wavelength and the signal intensity corresponding to the signal wavelength, it further includes: when the wavelength concentration value belongs to a predetermined wavelength range, determining that the fault type is a surface discharge fault.

[0055] In this embodiment, by detecting the wavelength concentration value of the visible light signal and comparing it with the predetermined wavelength range, the presence of a surface discharge fault can be accurately determined. Using the wavelength and intensity of the visible light signal to judge the fault type, without directly contacting the transformer or its internal components, non-contact fault detection can be achieved, which improves the safety to a certain extent and avoids cumbersome disassembly and inspection of the equipment.

[0056] As an alternative embodiment, when the wavelength concentration value does not belong to the predetermined wavelength range, after determining the first wavelength distance index of the wavelength concentration value from the predetermined wavelength value, it further includes: when the first wavelength distance index is greater than or equal to the wavelength predetermined index, determining the second wavelength distance index of the wavelength concentration value from the predetermined wavelength range; when the second wavelength distance index is less than the wavelength predetermined index, determining the frequency concentration value of the audible signal; when the third distance index of the frequency concentration value from the third predetermined frequency value is less than the frequency predetermined index, determining that the fault type is a surface discharge fault.

[0057] In this embodiment, if the first wavelength distance index is greater than or equal to the wavelength predetermined index, in this case, the second wavelength distance index of the wavelength concentration value from the predetermined wavelength range can be calculated, and this index can represent the proximity between the wavelength concentration value and the predetermined wavelength range; if the second wavelength distance index is less than the wavelength predetermined index, in this case, the frequency concentration value of the audible signal can be determined. Finally, if the third distance index between the frequency concentration value and the third predetermined frequency value is less than the frequency predetermined index, the fault type can be determined as the surface discharge fault.

[0058] It should be noted that by comparing the wavelength concentration value, the frequency concentration value, and the distance indices from the predetermined wavelength and frequency, and determining the first and second wavelength distance indices, the accuracy of fault type judgment can be enhanced. It helps to more accurately determine the fault type as the surface discharge fault, thus providing more explicit guidance for subsequent fault handling and maintenance work.

[0059] As an optional embodiment, after determining the fault type of the fault in the transformer cavity based on the audible signal, it further includes: determining the fault handling method corresponding to the fault type; sending a fault handling instruction to the terminal device corresponding to the fault handling method, where the fault handling instruction carries the fault handling method.

[0060] In this embodiment, by analyzing the audible signal and combining relevant fault diagnosis methods, the fault type in the transformer cavity can be determined, such as surface discharge, arc discharge, partial discharge, etc. Further, according to the fault type, combined with the operation requirements and operation procedures of the transformer, the fault handling method suitable for this fault type can be determined. For example, for the surface discharge fault, it may be necessary to replace or repair the insulating material. Finally, the determined fault handling method can be converted into a fault handling instruction and sent to the terminal device corresponding to the fault handling method. The terminal device may be a control system, a monitoring device, or other devices for performing operations.

[0061] It should be noted that by determining the fault handling method corresponding to the fault type, not only can the accuracy and efficiency of fault handling be ensured, the risks and losses in the fault troubleshooting and maintenance process be reduced, and the establishment of maintenance records and knowledge management be promoted, but it also helps to improve the reliability, maintainability, and safety of the equipment and system.

[0062] Based on the above embodiments and optional embodiments, an optional implementation manner is provided, which is specifically described below.

[0063] In related technologies, it's difficult to accurately identify faults within the transformer cavity. For example, when a transformer experiences an internal fault, the frequency band of the acoustic signal and the spectrum of the optical signal will change. Using audible and visible signals as characteristic indicators for state detection can help determine the fault state and type. However, the characteristic signals studied in related technologies are relatively simple, making it difficult to accurately assess the equipment state based on a single state variable. Furthermore, the differences between different defect types are not studied.

[0064] In view of this, an optional embodiment of the present invention provides a method for determining transformer faults, which can be understood as designing a method for distinguishing transformer discharge types based on the fusion of audible sound and visible light signals, which has strong theoretical and practical significance.

[0065] The optional implementation methods of this application are described in detail below.

[0066] S1, collecting visible light signals in the transformer cavity;

[0067] S2. Determine the signal wavelength of the visible light signal and the signal intensity corresponding to the signal wavelength;

[0068] S3. Determine a wavelength concentration value of the visible light signal based on the signal wavelength and the signal intensity corresponding to the signal wavelength;

[0069] S4. If the wavelength concentration value does not belong to the predetermined wavelength interval, determining a first wavelength distance index of the wavelength concentration value from the predetermined wavelength value;

[0070] It should be noted that after determining a first wavelength distance index between the wavelength concentration value and a predetermined wavelength value, the method further includes: if the first wavelength distance index is greater than or equal to the predetermined wavelength index, determining a second wavelength distance index between the wavelength concentration value and a predetermined wavelength range. If the second wavelength distance index is less than the predetermined wavelength index, determining a frequency concentration value of the audible sound signal; and if a third distance index between the frequency concentration value and a third predetermined frequency value is less than the predetermined frequency index, determining the fault type as a creeping discharge fault.

[0071] S5. When the first wavelength distance index is less than the predetermined wavelength index, collecting the audible sound signal in the transformer cavity;

[0072] S6. Determine the fault type of the transformer cavity fault based on the frequency concentration value.

[0073] It should be noted that the above-mentioned frequency concentration value can be determined through the following steps. For example, first, the signal frequency of the audible sound signal and the signal amplitude corresponding to the signal frequency are determined, and then the frequency concentration value of the audible sound signal is determined based on the signal frequency and the signal amplitude corresponding to the signal frequency.

[0074] S7. Determine the fault type of the fault in the transformer cavity based on the first frequency distance index and the second frequency distance index;

[0075] It should be noted that the first frequency distance index between the frequency concentration value and the first predetermined frequency value can be determined, and the second frequency distance index between the frequency concentration value and the second predetermined frequency value can be determined, where the first predetermined frequency value is the frequency value corresponding to the non-uniform field discharge fault, and the second predetermined frequency value is the frequency value corresponding to the uniform field discharge fault;

[0076] S8. When the first frequency distance index is less than the frequency predetermined index and the second frequency distance index is greater than or equal to the frequency predetermined index, determine that the fault type is a non-uniform field discharge fault, and / or, when the first frequency distance index is greater than or equal to the frequency predetermined index and the second frequency distance index is less than the frequency predetermined index, determine that the fault type is a uniform field discharge fault.

[0077] S9. Determine the fault handling method corresponding to the fault type, and send a fault handling instruction to the terminal device corresponding to the fault handling method, where the fault handling instruction carries the fault handling method.

[0078] For the above steps S1 - S9, the specific method includes the following steps:

[0079] A. Signal acquisition: Use sensors to collect audible and visible light signals of the transformer cavity, and transmit the collected audible and visible light signals to the signal analysis module;

[0080] B. Signal analysis: The signal analysis module receives the signals from the sensors, analyzes the signals and transmits the results to the result judgment module;

[0081] C. Result judgment: The result judgment module judges what type of fault has occurred in the transformer according to the received analysis results.

[0082] The specific steps of step A include the following steps:

[0083] A1. Install a visible light signal sensing module and an audible signal sensing module at appropriate positions on the outer wall of the cavity;

[0084] A2. The visible light signal sensing module collects the visible light signals of the cavity, and the audible signal sensing module collects the audible signals of the cavity;

[0085] A3. The visible light signal sensing module transmits the collected optical signals of the discharge to the visible light analysis module (3), and the audible signal sensing module transmits the collected acoustic signals of the discharge to the audible signal analysis module (4).

[0086] Step B specifically includes the following steps:

[0087] B1. The visible light signal analysis module analyzes the optical signal and calculates the wavelength and intensity of the collected visible light signal.

[0088] B2. The audible sound signal analysis module analyzes the sound signal and calculates the frequency and amplitude of the collected audible sound signal.

[0089] B3. The visible light signal analysis module compares the calculation results with the thresholds y1, y2, y3 - y4 (in the same predetermined wavelength range as above), and the audible sound signal analysis module compares the calculation results with the thresholds x1, x2, x3, and transmits the comparison results to the result judgment module.

[0090] Step C specifically includes the following steps:

[0091] C1. The result judgment module determines the fault type of the transformer according to the signal processing results. If the comparison result received by the result judgment module from the visible light analysis module is that the characteristic wavelengths of the visible light are concentrated in y3 - y4, it can be judged that the fault type of the transformer is surface discharge.

[0092] C2. If the comparison result received by the result judgment module from the visible light analysis module is that the characteristic wavelengths of the visible light are concentrated in y1 and y2, further judgment is made through the comparison result received from the audible sound signal analysis module. If the dominant frequency of the audible sound is concentrated in x1, it can be judged that the fault type of the transformer is extremely uneven field discharge. If the dominant frequency of the audible sound is concentrated in x2, it can be judged that the fault type of the transformer is uniform field discharge.

[0093] The specific method content described above is mainly a strategy for distinguishing the discharge types of transformers based on the fusion of audible sound and visible light signals. The idea of using the signal characteristics under different discharge forms of the transformer to solve the problem of judging the discharge type of the transformer is that the signal acquisition part uses a visible light signal sensing module and an audible sound signal sensing module for comprehensive acquisition. Therefore, faults that cannot be distinguished by visible light signals or audible sounds alone can be discriminated by combining the two signals. Combining the audible sound signal and the visible light signal is more conducive to assisting in judging its fault state and type, providing a new means for transformer condition monitoring.

[0094] Through the above optional implementation manners, at least the following beneficial effects can be achieved:

[0095] (1) Since the fault type of the transformer cavity can be determined based on the audible sound signal, by analyzing the audible sound signal in the transformer cavity, potential fault conditions can be detected early. Different types of faults usually produce specific sound characteristics. Using sound diagnosis, faults can be detected at the early stage of fault development, avoiding further deterioration of the faults and causing greater damage. By promptly identifying faults through sound diagnosis technology and taking corresponding maintenance measures, potential electrical accidents and shutdowns can be avoided, and the service life of the transformer can be extended;

[0096] (2) By determining the wavelength concentration value of the visible light signal, not only can the spectral characteristics of the signal be deeply understood, which helps to understand the characteristics and change trends of the signal and provides a basis for analyzing and interpreting the behavior of the visible light signal, but also abnormal wavelength or frequency components that may exist in the signal can be detected, so as to detect potential fault conditions early, perform accurate fault diagnosis, and take corresponding repair and restoration measures, thus solving the technical problem in the related art that it is difficult to accurately determine the faults in the transformer cavity;

[0097] (3) Since the fault type of the transformer cavity can be determined based on the frequency concentration value, that is, by comparing and matching the frequency concentration value with the sound frequency characteristics of known fault types, not only can the possible fault type be initially judged, but it also helps to improve the accuracy and efficiency of fault diagnosis, guide maintenance and preventive maintenance work, and promote the safety and reliability of the transformer system.

[0098] It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the present invention is not limited by the described action sequence, because according to the present invention, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0099] Through the description of the above embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by means of software plus a necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disc), and includes several instructions to enable a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0100] Example 2

[0101] According to an embodiment of the present invention, there is also provided an apparatus for implementing the above-mentioned transformer fault determination method. Figure 2 It is a structural block diagram of a transformer fault determination apparatus according to an embodiment of the present invention, as Figure 2 shown. The apparatus includes: a first acquisition module 202, a first determination module 204, a second determination module 206, a third determination module 208, a second acquisition module 210, and a fourth determination module 212. The following provides a detailed description of the apparatus.

[0102] The first acquisition module 202 is configured to acquire visible light signals inside the transformer cavity; the first determination module 204 is connected to the above-mentioned first acquisition module 202 and is configured to determine the signal wavelength of the visible light signal and the signal intensity corresponding to the signal wavelength; the second determination module 206 is connected to the above-mentioned first determination module 204 and is configured to determine the wavelength concentration value of the visible light signal based on the signal wavelength and the signal intensity corresponding to the signal wavelength; the third determination module 208 is connected to the above-mentioned second determination module 206 and is configured to determine the first wavelength distance index of the wavelength concentration value from a predetermined wavelength value when the wavelength concentration value does not belong to a predetermined wavelength interval; the second acquisition module 210 is connected to the above-mentioned third determination module 208 and is configured to acquire audible signals inside the transformer cavity when the first wavelength distance index is less than the wavelength predetermined index; the fourth determination module 212 is connected to the above-mentioned second acquisition module 210 and is configured to determine the fault type of the fault inside the transformer cavity based on the audible signals.

[0103] It should be noted here that the above-mentioned first acquisition module 202, first determination module 204, second determination module 206, third determination module 208, second acquisition module 210, and fourth determination module 212 correspond to steps S102 to S112 in implementing the transformer fault determination method. The examples and application scenarios implemented by multiple modules and corresponding steps are the same, but are not limited to the content disclosed in the above-mentioned embodiment 1.

[0104] Embodiment 3

[0105] According to another aspect of an embodiment of the present invention, there is also provided an electronic device, including: a processor; a memory for storing processor-executable instructions, wherein the processor is configured to execute the instructions to implement the above-mentioned transformer fault determination method in any one of the above.

[0106] Embodiment 4

[0107] According to another aspect of an embodiment of the present invention, there is also provided a computer-readable storage medium. When the instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device can execute the above-mentioned transformer fault determination method in any one of the above.

[0108] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0109] In the above embodiments of the present invention, the descriptions of each embodiment have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0110] In the several embodiments provided in the present application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only illustrative. For example, the division of the units can be a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be through some interfaces. The indirect coupling or communication connection of units or modules can be in an electrical or other form.

[0111] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0112] In addition, the functional units in each embodiment of the present invention can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0113] If the above integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to enable a computer device (such as a personal computer, a server or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: USB flash drives, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), mobile hard disks, magnetic disks or optical disks and other various media that can store program codes.

[0114] The above are only the preferred embodiments of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and modifications can be made, and these improvements and modifications should also be regarded as the protection scope of the present invention.

Claims

1. A method for determining a transformer fault, characterized in that: include: Collect visible light signals in the transformer cavity; Determining a signal wavelength of the visible light signal and a signal intensity corresponding to the signal wavelength; Determining a wavelength concentration value of the visible light signal according to the signal wavelength and the signal intensity corresponding to the signal wavelength; In a case where the wavelength concentration value does not belong to a predetermined wavelength interval, determining a first wavelength distance index between the wavelength concentration value and a predetermined wavelength value; When the first wavelength distance index is less than a predetermined wavelength index, collecting an audible sound signal in the transformer cavity; The fault type of the transformer cavity fault is determined based on the audible sound signal.

2. The method according to claim 1, characterized in that Determining the fault type of the transformer cavity fault according to the audible sound signal includes: determining a signal frequency of the audible sound signal and a signal amplitude corresponding to the signal frequency; Determining a frequency concentration value of the audible sound signal based on the signal frequency and the signal amplitude corresponding to the signal frequency; The fault type of the transformer cavity fault is determined according to the frequency concentration value.

3. The method according to claim 2, characterized in that Determining the fault type of the transformer cavity fault according to the frequency concentration value includes: Determining a first frequency distance index between the frequency concentration value and a first predetermined frequency value, and determining a second frequency distance index between the frequency concentration value and a second predetermined frequency value, wherein the first predetermined frequency value is a frequency value corresponding to an uneven field discharge fault, and the second predetermined frequency value is a frequency value corresponding to a uniform field discharge fault; The fault type of the transformer cavity fault is determined according to the first frequency distance index and the second frequency distance index.

4. The method according to claim 3, characterized in that Determining the fault type of the transformer cavity fault according to the frequency concentration value includes: When the first frequency distance index is less than the predetermined frequency index and the second frequency distance index is greater than or equal to the predetermined frequency index, determining that the fault type is the non-uniform field discharge fault, and / or When the first frequency distance index is greater than or equal to the predetermined frequency index and the second frequency distance index is less than the predetermined frequency index, the fault type is determined to be the uniform field discharge fault.

5. The method according to claim 1, wherein After determining the wavelength concentration value of the visible light signal according to the signal wavelength and the signal intensity corresponding to the signal wavelength, the method further includes: When the wavelength concentration value belongs to the predetermined wavelength range, the fault type is determined to be a creeping discharge fault.

6. The method according to claim 1, wherein In a case where the wavelength concentration value does not belong to the predetermined wavelength interval, after determining a first wavelength distance index between the wavelength concentration value and the predetermined wavelength value, the method further includes: In a case where the first wavelength distance index is greater than or equal to the predetermined wavelength index, determining a second wavelength distance index of the wavelength concentration value from the predetermined wavelength interval; determining a frequency concentration value of the audible sound signal when the second wavelength distance index is less than the predetermined wavelength index; When a third distance index between the frequency concentration value and the third predetermined frequency value is smaller than a predetermined frequency index, the fault type is determined to be a creeping discharge fault.

7. The method according to any one of claims 1 to 6, characterized in that After determining the fault type of the transformer cavity fault according to the audible sound signal, the method further includes: Determine a fault handling method corresponding to the fault type; Send a fault handling instruction to a terminal device corresponding to the fault handling method, wherein the fault handling instruction carries the fault handling method.

8. A transformer fault determination device, characterized in that: include: A first acquisition module, used for acquiring visible light signals in the transformer cavity; A first determining module is configured to determine a signal wavelength of the visible light signal and a signal intensity corresponding to the signal wavelength; A second determining module is configured to determine a wavelength concentration value of the visible light signal based on the signal wavelength and the signal intensity corresponding to the signal wavelength; a third determining module, configured to determine a first wavelength distance index between the wavelength concentration value and the predetermined wavelength value when the wavelength concentration value does not belong to the predetermined wavelength interval; a second acquisition module, configured to acquire an audible sound signal in the transformer cavity when the first wavelength distance index is less than a predetermined wavelength index; The fourth determining module is configured to determine a fault type of the transformer cavity fault according to the audible sound signal.

9. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the transformer fault determination method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that When the instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the transformer fault determination method according to any one of claims 1 to 7.

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