Transformer partial discharge positioning method and system based on UHF sensor

Abstract

The invention relates to the technical field of transformer monitoring, in particular to a transformer partial discharge positioning method based on UHF (Ultra High Frequency) sensors, which is characterized by comprising the following steps of: deploying three UHF sensor units which are arranged in an equilateral triangle in a partial discharge high-incidence area in a transformer; when local discharge occurs, synchronously detecting the micro-mechanical vibration amplitude and the UHF signal strength, and outputting an effective signal; and determining a unique space coordinate according to the arrival time of the three effective signals in combination with geometric constraints of an equilateral triangle. The three UHF sensor units arranged in the equilateral triangle shape are arranged in the transformer, the micro-mechanical vibration amplitude and the UHF signal strength are synchronously detected, the partial discharge detection reliability and the positioning precision are effectively improved, and false triggering is reduced.

Description

Technical Field

[0001] This invention belongs to the field of transformer monitoring technology, and in particular relates to a method and system for locating partial discharge in transformers based on a UHF sensor. Background Technology

[0002] In power systems, large oil-immersed power transformers, as key transmission and transformation equipment, directly impact the overall safety of the power grid due to their operational stability. Partial discharge is a core characteristic of early-stage insulation material degradation, especially when the discharge quantity is below ten picocoulombs, typically corresponding to the initial stage of latent defects such as internal microcracks, residual air gaps, or localized corona discharge. Although these weak discharge signals have low energy, they pose significant evolutionary risks. If they cannot be accurately captured and spatially located in their early stages, they can easily develop into serious faults such as inter-turn short circuits and winding breakdowns during long-term operation, causing substantial economic losses and safety threats. Therefore, developing technical solutions capable of reliably identifying and accurately locating minute partial discharges is a crucial step in shifting transformer condition-based maintenance from passive response to proactive early warning.

[0003] In practical partial discharge detection, UHF technology effectively avoids the shortcomings of traditional electrical methods, such as susceptibility to power frequency interference and response delays of acoustic methods, thus improving the real-time performance and environmental adaptability of detection. However, with the continuous increase in the accuracy requirements for early insulation defect diagnosis, especially for the monitoring of weak discharge signals, existing UHF sensing solutions have revealed fundamental limitations: the UHF electromagnetic signals generated by weak discharges attenuate significantly after passing through multiple layers of media such as transformer oil and insulating paperboard, falling far below the detection threshold of conventional UHF sensors; at the same time, due to limitations in antenna structure and RF front-end integration technology, it is difficult to embed them into areas prone to small discharges, such as winding layers and core gaps, leading to further signal attenuation during propagation.

[0004] More notably, under conditions of severely degraded signal-to-noise ratio, the positioning method based on time difference of arrival suffers from increased timing jitter, with time measurement errors often exceeding ten nanoseconds. This results in spatial positioning accuracy failing to meet the inspection standards for millimeter-level defect tracing. In existing technologies, detection mechanisms relying solely on UHF signals are unreliable in weak discharge scenarios, are susceptible to environmental noise interference leading to false triggering, and cannot effectively distinguish between real discharge signals and background interference, severely restricting the ability to accurately identify early defects. Summary of the Invention

[0005] The purpose of this invention is to provide a transformer partial discharge localization method and system based on a UHF sensor, which has the advantages of improving the detection reliability and localization accuracy of weak discharge signals and reducing false triggering. A first aspect of this invention is a transformer partial discharge localization method based on a UHF sensor, comprising the following steps: Three UHF sensor units arranged in an equilateral triangle are deployed in the high-incidence area of ​​partial discharge inside the transformer. Each unit is arranged in an equilateral triangle and the adjacent spacing is three centimeters. Each UHF sensor unit integrates a micromechanical vibration sensitive structure and a UHF antenna. When partial discharge occurs, the amplitude of micromechanical vibration and the intensity of UHF signal are detected simultaneously. Only when the amplitude of micromechanical vibration and the intensity of UHF signal simultaneously trigger the minimum threshold is an effective signal output. The unique spatial coordinates are determined based on the arrival times of the three valid signals and the geometric constraints of an equilateral triangle. If three independent localization operations are performed on the same suspected defect point, and the spatial deviation of the three results is lower than the minimum allowable deviation value, then the point is confirmed as a stable defect source.

[0006] As a further aspect of the present invention, if the spatial coordinates are located inside the triangle formed by the three UHF sensor units, they are considered as valid positioning results. The results are compared with the distribution map of typical defects inside the transformer. If the location belongs to the winding layer, the core grounding plate, or the bushing root, the results are retained; otherwise, no positioning operation is performed.

[0007] As a further aspect of the present invention, before the output of the valid signal, an initial triggering step is included: the micromechanical vibration sensitive structure and the UHF antenna independently acquire signals, and a hardware logic comparator determines whether both reach their respective preset minimum triggering thresholds simultaneously.

[0008] As a further aspect of the present invention, after the initial triggering step, a signal synchronization verification step is also included: using a high-precision timing circuit, the time difference between the arrival time of the rising edge of the micromechanical vibration signal and the UHF signal is determined. If the time difference is less than or equal to a preset synchronization tolerance threshold, it is determined to be a synchronization signal, and the subsequent positioning step is entered.

[0009] As a further aspect of the present invention, after the signal synchronization verification step, a feature matching verification step is also included: for the signal that has been determined to be synchronized, it is further verified whether the frequency energy distribution of the UHF signal is within the predetermined discharge characteristic frequency band, and at the same time, it is verified whether the time domain or frequency domain characteristics of the micromechanical vibration signal are consistent with the predetermined discharge vibration characteristics.

[0010] As a further aspect of the present invention, after the feature matching verification step, the core positioning step is entered: based on the signals of the three verified UHF sensor units, the arrival time difference between each pair is calculated, and combined with the geometric constraints of the equilateral triangle layout and the known propagation speed of the signal, a unique spatial coordinate solution that satisfies all spatiotemporal constraints is obtained.

[0011] As a further aspect of the present invention, after obtaining the unique spatial coordinate solution, a positioning result comparison is performed, and after the comparison is successful, three independent positioning operations are performed to complete the precise positioning.

[0012] As a further embodiment of the present invention, the micromechanical vibration sensitive structure in the UHF sensor unit is a microcantilever beam, one end of which is fixed to a silicon substrate, and the other end extends freely and is directly coupled to the radiating element of the UHF antenna. A capacitive displacement detection structure is provided between the bottom of the microcantilever beam and the surface of the silicon substrate to convert the displacement of the microcantilever beam into a voltage signal to characterize the vibration amplitude.

[0013] As a further aspect of the present invention, it also includes a discharge state analysis step: obtaining the current environmental parameters and the actual defect location and discharge characteristic parameters in the historical discharge record database; calculating the matching degree between the location result and the historical defect distribution map; if the matching degree is higher than the preset confidence threshold and the environmental parameters do not fluctuate drastically, then the confidence level of the result is improved.

[0014] Another aspect of the present invention provides a transformer partial discharge location system based on a UHF sensor, comprising: The sensor array consists of three UHF sensor units that integrate micromechanical vibration-sensitive structures, arranged in an equilateral triangle layout; The signal processing module is used to verify signal synchronization, feature matching, and triggering logic. The positioning calculation module calculates coordinates based on time difference and geometric constraints; The result verification module verifies the regional rationality and stability of the positioning results.

[0015] The beneficial effects of this invention are as follows: This invention deploys three UHF sensor units arranged in an equilateral triangle inside the transformer to simultaneously detect the amplitude of micromechanical vibration and the intensity of the UHF signal. It outputs a valid signal only when both trigger the minimum threshold simultaneously, and determines the spatial coordinates based on the arrival time and the geometric constraints of the equilateral triangle. This effectively improves the reliability and positioning accuracy of partial discharge detection and reduces false triggering. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A flowchart of a transformer partial discharge localization method based on a UHF sensor provided in an embodiment of the present invention. Detailed Implementation

[0018] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0019] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance. Example

[0020] This embodiment provides a transformer partial discharge localization method based on UHF sensors, including: S1, deploying three UHF sensor units arranged in an equilateral triangle in a high-incidence area of ​​partial discharge inside the transformer, with each unit arranged in an equilateral triangle and the adjacent spacing being three centimeters; each UHF sensor unit integrates a micromechanical vibration sensitive structure and a UHF antenna; S2, when a partial discharge occurs, simultaneously detecting the amplitude of micromechanical vibration and the intensity of the UHF signal, and outputting a valid signal only when the amplitude of micromechanical vibration and the intensity of the UHF signal simultaneously trigger the minimum threshold; S3, determining a unique spatial coordinate based on the arrival time of the three valid signals combined with the geometric constraints of the equilateral triangle; S4, performing three independent localization operations consecutively on the same suspected defect point, and if the spatial deviation of the three results is lower than the minimum allowable deviation value, then the point is confirmed as a stable defect source.

[0021] For ease of understanding, the following explains some key terms in this embodiment: A UHF sensor unit is a device capable of sensing and converting ultra-high frequency electromagnetic wave signals. It integrates a UHF antenna for detecting electromagnetic waves generated by partial discharge, and a micro-mechanical vibration-sensitive structure for detecting mechanical vibrations caused by partial discharge. The micro-mechanical vibration-sensitive structure is a structure fabricated based on microelectromechanical systems (MEMS) technology that is sensitive to minute mechanical vibrations, converting the mechanical vibrations caused by partial discharge into measurable electrical signals. The UHF antenna is a device operating at ultra-high frequency (UHF)... Electromagnetic wave receiving devices operating in the frequency band (typically 300MHz to 3GHz) are used to capture high-frequency electromagnetic pulses radiated during partial discharge. High-incidence areas of partial discharge refer to specific areas within the transformer's internal insulation structure where partial discharge events are more likely to occur due to factors such as concentrated electric fields, material defects, or manufacturing processes. Examples include winding layers, core grounding plates, or bushing roots. An equilateral triangle layout refers to the arrangement of three UHF sensor units in space at the vertices of an equilateral triangle, providing a fixed spatial reference for subsequent geometric positioning calculations. Micromechanical vibration amplitude refers to the intensity of the mechanical vibration signal detected by the micromechanical vibration-sensitive structure, reflecting the mechanical impact energy generated by partial discharge. UHF signal strength refers to the power or voltage amplitude of the ultra-high frequency electromagnetic wave signal received by the UHF antenna, reflecting the electromagnetic radiation energy generated by partial discharge. The minimum threshold is a preset minimum value used to determine whether the micromechanical vibration amplitude or UHF signal strength meets the effective detection standard. A signal is considered valid only when its strength exceeds this threshold. A valid signal is one that, after synchronous detection and threshold judgment, is confirmed as being generated by a partial discharge event and can be used for subsequent location calculations. The arrival time is the moment when the partial discharge signal travels from the discharge source to each UHF sensor unit for detection. The equilateral triangle geometric constraint is the geometric restriction imposed when solving for the spatial coordinates of the partial discharge source using their fixed relative positional relationship, given that the three UHF sensor units are arranged in an equilateral triangle. The unique spatial coordinates are the location of the partial discharge source, uniquely determined in the three-dimensional space inside the transformer, calculated by the positioning algorithm. The spatial deviation is the distance difference between the spatial coordinate results obtained from multiple independent positioning operations. The minimum allowable deviation value is the preset maximum permissible spatial deviation used to determine whether multiple positioning results have consistency. A stable defect source is a partial discharge defect point whose spatial coordinate results are consistent and whose spatial deviation is lower than the minimum allowable deviation value, verified by multiple independent positioning operations.

[0022] This embodiment provides a transformer partial discharge location method based on UHF sensors. Specifically, three UHF sensor units arranged in an equilateral triangle are deployed in a high-incidence area of ​​partial discharge inside the transformer. Each unit is arranged in an equilateral triangle with an adjacent spacing of three centimeters. As a preferred implementation, the sensor units can be miniaturized, for example, by encapsulating the UHF antenna and micro-mechanical vibration sensitive structure in a single chip or micro-module using integrated circuit technology. During deployment, the three sensor units can be fixed in a specific position inside the transformer, such as between windings or near the core, using a robotic arm or a pre-set mounting bracket. The spacing of the equilateral triangles can be adjusted according to the internal space of the transformer and the expected positioning accuracy. For example, the spacing can be manually measured and fixed during deployment.

[0023] Furthermore, each UHF sensor unit integrates a micromechanical vibration-sensitive structure and a UHF antenna. When a local discharge occurs, it synchronously detects the amplitude of the micromechanical vibration and the strength of the UHF signal. Only when the amplitude of the micromechanical vibration and the strength of the UHF signal simultaneously trigger the minimum threshold is a valid signal output. Specifically, signal detection can be performed by an independent vibration sensor and a UHF receiver. The vibration sensor can be a piezoelectric sensor that converts mechanical vibration into a voltage signal, while the UHF receiver converts the received electromagnetic wave into an electrical signal. These two signals can be amplified and filtered by their respective analog front-ends. Synchronous detection can be achieved by inputting the two signals into independent comparators. Each comparator is compared with a preset minimum threshold. When both comparators output a high level simultaneously (indicating that the signal exceeds the threshold), a logic gate (e.g., an AND gate) can output a valid signal.

[0024] Therefore, a unique spatial coordinate can be determined based on the arrival times of the three valid signals and the geometric constraints of an equilateral triangle. For example, when each sensor unit outputs a valid signal, it can record the current timestamp. These timestamps are sent to a central processing unit. After receiving the arrival times of the valid signals from the three sensor units, the central processing unit can use the trilateration method or time difference positioning algorithm to perform calculations. It can be assumed that the signal propagation speed is known. By calculating the distance from the power source to each sensor and combining it with the equilateral triangle layout of the three sensor units, a set of nonlinear equations can be established. Through iterative solutions or numerical methods, the unique spatial coordinates that satisfy these distance and geometric constraints can be obtained.

[0025] As a preferred implementation, three independent localization operations are performed consecutively on the same suspected defect point. If the spatial deviation of the three results is lower than the minimum allowable deviation value, the point is confirmed as a stable defect source. Specifically, after obtaining a preliminary localization result, the system can wait for a period of time or, under different triggering conditions, execute the complete localization process again to obtain the second and third localization results. Each localization operation should be performed independently, that is, the entire process from signal acquisition to coordinate calculation. After obtaining three spatial coordinates, the Euclidean distance or Manhattan distance between the three coordinate points can be calculated to evaluate the spatial deviation between them. If the distance between all pairs is less than the preset minimum allowable deviation value, the suspected defect point is considered a stable and reliable defect source.

[0026] This application deploys a compact UHF sensor unit in a region where discharge events occur frequently inside the transformer, and integrates a micromechanical vibration-sensitive structure with a UHF antenna. This enables simultaneous dual detection of low-intensity discharge signals, effectively overcoming the problem of significant intensity attenuation of a single UHF signal when propagating in multiple media. Combined with equilateral triangle geometric constraints and multiple independent positioning verifications, the spatial positioning accuracy and reliability of partial discharges are improved, thus meeting the need for precise tracing of millimeter-level early insulation defects.

[0027] In some of the solutions described above in this application, a positioning method is proposed to determine the discharge location. However, during its implementation, the positioning result may be located in an invalid sensor layout area or an atypical defect location, leading to invalid operation or incorrect judgment. In response, this application further proposes a transformer partial discharge positioning method, which verifies the effectiveness of the positioning result and filters based on the distribution of typical defects to ensure that the positioning operation is only performed in high-risk areas.

[0028] Specifically, if the spatial coordinates are located inside the triangle formed by the three UHF sensor units, it is considered a valid positioning result. This step aims to make a geometric validity judgment on the initially obtained partial discharge spatial coordinates. For example, the centroid coordinates of the point to be located relative to the three UHF sensor units can be calculated. If all centroid coordinates are between 0 and 1, it indicates that the point is located inside the triangle. Alternatively, the cross product principle can be used to determine whether the cross product direction of the vectors formed by the lines connecting the point to be located and the sensor units is consistent. If they are consistent, the point is inside the triangle. In this way, false positioning results that fall outside the effective coverage area of ​​the sensor array due to signal reflection, multipath effect, or calculation error can be effectively eliminated, thereby improving the reliability of positioning.

[0029] Based on this, the results are compared with a typical defect distribution map inside the transformer. The typical defect distribution map inside the transformer is a pre-established database or three-dimensional model containing information on common high-incidence areas of partial discharge inside the transformer. For example, the map can be a digital model that stores the three-dimensional coordinate range or geometric definition of key parts such as winding layers, core grounding plates, and bushing roots; or it can be a logical mapping table that divides the internal space of the transformer into areas of different risk levels based on historical fault data and expert experience. By matching the located spatial coordinates with the map, it can be determined whether the discharge point is located in a critical area inside the transformer with weak insulation or prone to failure.

[0030] If the comparison results show that the location belongs to the winding layer, core grounding plate, or bushing root, the location result is retained; otherwise, no location operation is performed. For example, the system can execute a spatial query algorithm to determine whether the location point falls within the geometric boundary of the predefined "winding layer" area in the map, or whether it overlaps with the coordinate range of "core grounding plate" or "bushing root". If the location point is located in one of these typical defect areas, the discharge event is considered to have high diagnostic value and potential risk, and its location result will be further processed and analyzed. Conversely, if the location point is located in an atypical or low-risk area, the result will be filtered out to avoid resource investment and misjudgment of unimportant discharge events.

[0031] Through the above technical solution, this application can effectively solve the problem that the positioning results may be located in the invalid area of ​​the sensor layout or the location of atypical defects. First, by judging whether the spatial coordinates are located inside the triangle formed by the three UHF sensor units, the geometric rationality of the positioning results is ensured, avoiding subsequent processing of invalid positioning results that are outside the effective coverage area of ​​the sensors or caused by abnormal signals. Second, the effective positioning results are compared with the distribution map of typical defects inside the transformer, and only the positioning results located in high-risk areas such as the winding layers, the iron core grounding plate, or the bushing root are retained. This allows the positioning system to intelligently screen out partial discharge events with practical diagnostic significance by combining the structural characteristics and fault modes of the transformer. This secondary screening mechanism based on geometric constraints and expert knowledge significantly improves the accuracy and practicality of the positioning results, avoids misjudgment and waste of resources for non-critical areas or false discharge points, and makes the diagnosis of transformer partial discharge more efficient and accurate.

[0032] In some of the embodiments described above in this application, a method for positioning based on valid signals is proposed. However, during its implementation, signal triggering may be inaccurate, leading to misjudgment and positioning errors.

[0033] In response, this application further proposes an initial triggering step before outputting a valid signal: the micromechanical vibration sensitive structure and the UHF antenna independently acquire signals, and a hardware logic comparator determines whether both reach their respective preset minimum triggering thresholds simultaneously.

[0034] The initial triggering step, as a prerequisite for the signal processing flow, aims to preliminarily screen potential partial discharge events and avoid transmitting non-discharge signals or noise signals triggered by a single sensor to the subsequent complex positioning calculation stage, thereby improving the system's processing efficiency and positioning accuracy. This step can be implemented in various ways. For example, an analog comparator circuit can be designed to output a trigger pulse when the analog voltage values ​​of the micromechanical vibration signal and the UHF signal simultaneously exceed a preset threshold; or, the analog signal can be converted into a digital signal by an analog-to-digital converter (ADC), and logic gates can be configured inside a field-programmable gate array (FPGA) or complex programmable logic device (CPLD) for real-time comparison. When the two digital signals simultaneously meet the threshold condition, a digital trigger signal is generated.

[0035] The micromechanical vibration-sensitive structure and the UHF antenna acquire signals independently to ensure that signals generated by two different physical mechanisms (mechanical vibration and electromagnetic radiation) can be captured independently and without interference. This independence is crucial for accurately determining signal synchronization and avoids false triggering caused by internal coupling or signal crosstalk of the sensor. The methods to achieve independent acquisition include, but are not limited to: maintaining a certain distance between the micromechanical vibration-sensitive structure and the UHF antenna physically and using independent signal acquisition circuits, amplifiers, and analog-to-digital converters to ensure complete separation of signal paths; or, providing good electromagnetic shielding for the UHF antenna and its front-end circuit to reduce electromagnetic interference to the micromechanical vibration-sensitive structure. At the same time, the micromechanical vibration signal can be transmitted differentially to enhance its anti-common-mode interference capability.

[0036] The simultaneous attainment of their respective preset minimum trigger thresholds is a preliminary and crucial joint criterion for determining whether an event constitutes a valid partial discharge. By requiring the signal strengths of two different physical phenomena (mechanical vibration and UHF electromagnetic radiation) to reach a certain level, the recognition rate of real discharge events can be significantly improved, while effectively suppressing false triggers caused by a single noise source (such as mechanical vibration noise or environmental electromagnetic noise). These thresholds can be achieved through adjustable threshold settings, i.e., setting programmable or adjustable reference voltages or digital values ​​as thresholds in hardware comparators or digital logic, and calibrating them according to the transformer's operating environment, noise level, and desired detection sensitivity.

[0037] By introducing an initial triggering step before outputting a valid signal, and using a hardware logic comparator to synchronously judge the signals independently acquired by the micromechanical vibration-sensitive structure and the UHF antenna, a valid signal is output only when both signals simultaneously reach their respective preset minimum triggering thresholds. This effectively solves the problem of inaccurate signal triggering and significantly reduces the risk of misjudgment and positioning errors. Through rigorous joint screening in the early stages of signal processing, this application can more accurately identify real partial discharge events, laying a solid foundation for subsequent precise spatial positioning, thereby improving the reliability and efficiency of the entire positioning method.

[0038] In some of the solutions described above in this application, an initial triggering step is proposed to determine whether the micromechanical vibration signal and the UHF signal have simultaneously reached their respective preset minimum triggering thresholds. However, in the implementation process, due to signal propagation delay, noise interference, or measurement errors, even if the signals are triggered simultaneously, their rising edge arrival times may differ significantly, leading to misjudgment as synchronization signals, which in turn affects the accuracy and reliability of subsequent positioning.

[0039] In response, this application further proposes that after the initial triggering step, a signal synchronization verification step is also included: using a high-precision timing circuit, the time difference between the arrival time of the rising edge of the micro-mechanical vibration signal and the UHF signal is determined. If the time difference is less than or equal to a preset synchronization tolerance threshold, it is determined to be a synchronization signal and proceeds to the subsequent positioning step.

[0040] The signal synchronization verification step aims to ensure a high degree of temporal consistency between the micromechanical vibration signal and the UHF signal, thereby eliminating false triggers caused by noise, environmental interference, or non-discharge events, and significantly improving the accuracy and reliability of subsequent positioning. This step can be implemented in various ways. For example, hardware logic circuits can be used, with comparators and timing logic gates, to trigger the synchronization verification mechanism when the rising edges of the two signals appear successively within a very short time. Alternatively, it can be implemented using an embedded processor or field-programmable gate array (FPGA), where the digitized sampling data of the two signals are input into the processing unit, and the timing relationship of their rising edges is analyzed through software algorithms or hardware description languages ​​(HDL).

[0041] The time difference between the arrival times of the rising edges of the micromechanical vibration signal and the UHF signal refers to the time interval on the time axis between the starting points (i.e., rising edges) of the waveforms of the micromechanical vibration signal and the UHF signal generated by the partial discharge event, which rise significantly from the baseline. This time difference is measured by recording the rising edges of the two signals using a high-precision timing circuit, and then calculating the difference between the two timestamps. For example, when the voltage of the micromechanical vibration signal first exceeds a certain preset small threshold, time T1 is recorded, and when the voltage of the UHF signal first exceeds another preset small threshold, time T2 is recorded. Then the time difference is |T1-T2|.

[0042] The preset synchronization tolerance threshold is used to define the maximum allowable time deviation between two signals that are considered "synchronized". This threshold needs to be determined comprehensively based on the signal propagation characteristics inside the transformer, the sensor response speed, and the desired positioning accuracy. The determination method can include experimental calibration, measuring the actual signal time difference under the condition of knowing the power supply location and propagation path, and setting a reasonable upper limit by combining system noise and measurement error; or it can be calculated based on a theoretical model, taking into account factors such as the difference in signal propagation speed in different media and the sensor's own response delay, to derive the maximum allowable time deviation.

[0043] When the time difference between the measured micromechanical vibration signal and the arrival time of the rising edge of the UHF signal is less than or equal to a preset synchronization tolerance threshold, the system will determine it as a synchronization signal. This means that the system considers these two signals to be valid signals generated synchronously by the same partial discharge event. Only valid signals determined to be synchronized will be sent to subsequent positioning steps for processing to determine the spatial coordinates of the partial discharge source. This ensures that the input data for positioning calculations is reliable and time-consistent, thereby avoiding mispositioning caused by asynchronous signals.

[0044] Through the above technical solution, this application can accurately verify the time consistency of micromechanical vibration signals and UHF signals, ensuring that only truly synchronized signals enter the subsequent positioning process. Specifically, a signal synchronization verification step is added after the initial triggering step to compensate for the deficiency that the initial triggering, which is based solely on threshold judgment, may ignore time accuracy. A high-precision timing circuit is used to accurately measure the time difference, effectively reducing errors caused by measurement jitter. The time difference at the arrival time of the signal rising edge is judged, focusing on the signal starting point rather than the overall waveform, ensuring that the judgment is based on the actual start time of the signal. A synchronization tolerance threshold is set to allow reasonable tolerance but avoid misjudgment due to minor differences. Only when the time difference is less than or equal to the preset threshold is it determined to be a synchronized signal, eliminating asynchronous interference. Finally, it enters the subsequent positioning step, ensuring that the positioning process is based on a reliable synchronization signal, enhancing the stability and accuracy of the overall positioning. This significantly reduces the misjudgment rate caused by signal asynchrony and improves the quality of input data for subsequent positioning calculations, thus making the final partial discharge positioning result more accurate and reliable, especially for the identification and positioning of weak discharge signals.

[0045] In some of the solutions described above in this application, a signal synchronization verification step is proposed to ensure that the micromechanical vibration signal and the UHF signal are synchronized in time. However, in this process, even if the signals are synchronized, there may be non-discharge signals or interference signals that are misjudged as valid signals, leading to positioning errors or false alarms.

[0046] In this regard, this application further proposes that, after the signal synchronization verification step, a feature matching verification step is also included: for the signal that has been determined to be synchronized, it is further verified whether the frequency energy distribution of the UHF signal is within the predetermined discharge characteristic frequency band, and at the same time, it is verified whether the time domain or frequency domain characteristics of the micromechanical vibration signal are consistent with the predetermined discharge vibration characteristics.

[0047] Specifically, the feature matching verification step aims to further identify signals that have passed time synchronization verification in order to distinguish between real partial discharge signals and various interference signals. Its core lies in using the unique physical characteristics of partial discharge events to perform pattern recognition on UHF electromagnetic signals and micromechanical vibration signals, thereby improving the accuracy and reliability of signal determination. This step can be implemented by a digital signal processor (DSP) or a field-programmable gate array (FPGA). It receives the synchronized UHF signal and micromechanical vibration signal and executes a preset algorithm, such as Fourier transform and wavelet analysis, to extract the frequency and time-domain features of the signal and compare them with the discharge feature template stored in memory. Alternatively, this step can also be implemented by a model based on machine learning or deep learning. During the training phase, a classifier is trained using a large number of known discharge signal and interference signal samples, enabling it to automatically learn and identify the complex features of discharge signals. In practical applications, the synchronized signal is input into the trained model, and the model outputs the judgment result of whether the signal is a discharge signal.

[0048] Furthermore, verifying whether the frequency energy distribution of the UHF signal is within the predetermined discharge characteristic frequency band is based on the fact that UHF signals generated by partial discharge have specific frequency ranges and energy distribution characteristics, which are significantly different from the spectral characteristics of environmental noise or other electrical interference signals. By verifying whether the frequency energy distribution of the UHF signal conforms to these predetermined characteristics, non-discharge-induced UHF signals, such as broadband noise generated by radio broadcasting, mobile phone communication, or switching operations, can be effectively eliminated. This verification can be performed by decomposing the spectrum of the UHF signal using a bandpass filter bank, and then calculating the energy proportion in each frequency band. The predetermined discharge characteristic frequency band is usually between 300MHz and 3GHz, and the energy will be significantly concentrated in certain specific sub-frequency bands. If the signal energy is mainly concentrated in these specific frequency bands, it is considered to conform to the discharge characteristics. In addition, the UHF signal can also be converted from the time domain to the frequency domain by Fast Fourier Transform (FFT), and then its power spectral density (PSD) can be analyzed. By setting multiple frequency windows, the energy integral in each window is calculated, and correlation analysis or Euclidean distance calculation is performed with the preset discharge characteristic spectrum template to determine its matching degree.

[0049] Meanwhile, verifying whether the time-domain or frequency-domain characteristics of the micromechanical vibration signal match the predetermined discharge vibration characteristics is based on the fact that when partial discharge occurs, in addition to generating UHF electromagnetic waves, it is also accompanied by weak mechanical vibrations or sound waves. These vibration signals have unique patterns related to the discharge event in the time domain (such as pulse width, rise time, and attenuation characteristics) and frequency domain (such as dominant frequency and harmonic components). By analyzing these characteristics, it can be further confirmed whether the signal source is a partial discharge, and non-discharge vibrations caused by normal transformer operation vibration, external mechanical impact, or electromagnetic force can be ruled out. In the time domain, parameters such as the envelope, pulse width, peak value and root mean square ratio (PAPR) of the vibration signal can be analyzed. For example, vibrations caused by partial discharge are usually manifested as short-duration, high-amplitude impact pulses. By setting the threshold range of these parameters, it can be determined whether the signal conforms to the characteristics of discharge vibration. In the frequency domain, spectral analysis can be performed on the micromechanical vibration signal to identify its dominant frequency components and harmonic distribution. Vibrations caused by partial discharge often have significant energy in the ultrasonic frequency band (such as 20kHz to 200kHz) and may be accompanied by specific harmonic structures. By comparing the spectrum of the signal with the preset discharge vibration spectrum template, its matching degree can be determined.

[0050] The above technical solution introduces a feature matching verification step after signal synchronization verification to further identify the features of the UHF signal and micromechanical vibration signal that have been determined to be synchronized. This solution utilizes the physical characteristic that partial discharge events simultaneously generate UHF signals with specific frequency energy distributions and micromechanical vibration signals with specific time-domain or frequency-domain characteristics. Through a dual feature matching mechanism, it effectively distinguishes between real partial discharge signals and various interference signals. This significantly reduces the risk of non-discharge signals being misjudged as valid signals, thereby avoiding positioning errors or false alarms caused by interference signals. It improves the accuracy and reliability of transformer partial discharge positioning, making subsequent positioning results more realistic and credible, and providing a more solid data foundation for transformer condition-based maintenance.

[0051] In some of the embodiments described above in this application, a feature matching verification step is proposed to ensure that the signal is a valid discharge signal. However, in its implementation, the positioning calculation may result in insufficient positioning accuracy due to time measurement errors and lack of geometric constraints, which cannot meet the requirements of high-precision positioning.

[0052] In response, this application further proposes to proceed to the core positioning step after the feature matching verification step: based on the signals of the three verified UHF sensor units, calculate the arrival time difference between each pair, and combine the geometric constraints of the equilateral triangle layout with the known propagation speed of the signal to solve for the unique spatial coordinate solution that satisfies all spatiotemporal constraints.

[0053] Specifically, this core positioning step is first based on the signals from three verified UHF sensor units. "Verified" here means that these signals have successfully passed the aforementioned initial triggering, signal synchronization verification, and feature matching verification steps. This means that these signals not only meet the minimum triggering threshold, but also have strict synchronization between their micromechanical vibration signals and UHF signals, and the frequency energy distribution of the UHF signals is within the predetermined discharge characteristic frequency band. At the same time, the time domain or frequency domain characteristics of the micromechanical vibration signals also match the predetermined discharge vibration characteristics. This rigorous pre-verification ensures that the signals used for positioning are real, reliable, and high-quality signals with discharge characteristics, thus laying the foundation for subsequent accurate calculations.

[0054] Next, the arrival time difference between each pair is calculated. The arrival time difference refers to the time difference between the arrival of the partial discharge signal at any two UHF sensor units. Obtaining these time differences is key information for positioning. For example, the arrival time difference can be obtained by performing cross-correlation on the two signals and the time delay corresponding to the peak value of the cross-correlation function. Alternatively, the time point when the rising edge of the signal first reaches a preset threshold can be recorded, and then the difference between these time points can be calculated. These time differences reflect the relative distance difference between the discharge source and each sensor unit.

[0055] Based on this, and combined with the geometric constraints of the equilateral triangle layout, the three UHF sensor units are arranged in an equilateral triangle with an adjacent spacing of three centimeters. This precise and known geometric configuration provides strong spatial constraints for positioning. By utilizing this fixed geometric relationship, the positioning problem can be transformed from a general TDOA (Time Difference of Arrival) problem with possible multiple solutions into a specific problem with a known sensor geometry, thereby effectively narrowing the solution space and reducing the ambiguity of positioning.

[0056] Meanwhile, combined with the known propagation speed of the signal, the propagation speed of the partial discharge signal in the transformer's internal medium (such as transformer oil) is known in advance or measurable. By multiplying the measured arrival time difference by the signal propagation speed, the time difference can be converted into a distance difference, thereby mapping information from the time domain to the spatial domain. For example, the average propagation speed of the UHF signal in transformer oil and insulating materials can be determined by conducting experimental measurements or simulation calculations before the transformer is put into operation; or, considering the influence of environmental factors such as temperature and pressure on the propagation speed, these parameters can be monitored in real time by built-in sensors, and the preset propagation speed can be dynamically corrected.

[0057] Finally, a unique spatial coordinate solution that satisfies all spatiotemporal constraints is obtained. By comprehensively utilizing the arrival time difference between each pair of sensors, the equilateral triangle geometric layout of the sensor units, and the propagation speed of the signal in the medium, a set of mathematical equations can be constructed (e.g., based on the hyperbola intersection method or the least squares method). The solution of this set of equations is the precise three-dimensional spatial coordinate of the partial discharge source. Because it combines multiple constraints, including time information (arrival time difference), spatial information (sensor geometric layout), and physical information (propagation speed), it can ensure that the obtained spatial coordinates are unique and accurate.

[0058] Through the above technical solution, after rigorous signal verification, by utilizing the precise arrival time difference of three UHF sensor units, combined with their preset equilateral triangle geometric layout and the known propagation speed of the signal inside the transformer, a highly constrained positioning model can be constructed. This enables the system to overcome the problem of insufficient positioning accuracy caused by time measurement errors and lack of sufficient geometric constraints in traditional positioning methods. By closely combining time information, spatial information, and physical propagation characteristics, this solution can accurately calculate the unique spatial coordinates of the partial discharge source, significantly improving the positioning accuracy and reliability of weak partial discharges inside the transformer, and providing solid technical support for the accurate tracing of early defects.

[0059] In some of the solutions described above in this application, a unique spatial coordinate solution is proposed to locate the partial discharge point of the transformer. However, in this process, the single location result may have random errors or instability, which cannot ensure the accuracy and reliability of the location, resulting in insufficient accuracy of subsequent defect source confirmation.

[0060] In response, this application further proposes that after obtaining the unique spatial coordinate solution, a positioning result comparison is performed, and after the comparison is passed, three independent positioning operations are performed to complete the precise positioning. Specifically, performing a positioning result comparison refers to the process of evaluating the validity, rationality, or confidence of the unique spatial coordinate solution obtained through the positioning calculation module. Its purpose is to filter out unreliable results that may be caused by noise, interference, or calculation errors before using the positioning results for subsequent operations. For example, a preset reasonable area range can be set, such as the physical boundary inside the transformer or a known high-incidence area of ​​defects. If the calculated spatial coordinates exceed this range, they are determined to be invalid results. Alternatively, they can be compared with historical data or empirical models. If the positioning result deviates significantly from the known typical defect distribution map, further verification or rejection may be required. In addition, internal evaluation indicators of the positioning algorithm can also be used, such as the covariance matrix or confidence interval of the positioning error. If these indicators exceed a preset threshold, the positioning result is considered unreliable.

[0061] Once the positioning result passes the comparison, it means that the positioning result has passed the above verification and is considered valid, reasonable, and credible. It can then proceed to the subsequent precise positioning process. Based on this, three independent positioning operations are performed. The aim is to reduce the random errors and uncertainties that may exist in a single positioning by repeatedly executing the positioning process, thereby improving the accuracy and stability of the final positioning result. Independence means that each operation should eliminate as much as possible the systematic bias that may be introduced by the previous operation. For example, three complete positioning processes can be performed consecutively in a short period of time, with each process from signal acquisition and processing to coordinate calculation performed independently to obtain three sets of independent positioning coordinates. Alternatively, different signal processing parameters or algorithm variants can be used to perform three independent positioning calculations on the same set of raw signal data to evaluate the consistency of results under different processing methods. Through the above comparison and repeated operations, a spatial coordinate of the partial discharge point with high confidence, low error, and stability is finally obtained, thereby completing the precise positioning.

[0062] Through the above technical solution, after obtaining a unique spatial coordinate solution, the positioning results are first compared. This effectively filters out positioning results that meet preset rationality or confidence standards, avoiding the introduction of unreliable results caused by noise, interference, or calculation errors into subsequent processes. For example, by comparing the positioning results with the distribution map of typical defects inside the transformer, if the location does not belong to high-incidence areas such as winding layers, core grounding plates, or bushing roots, no positioning operation is performed, thus ensuring the physical rationality of the positioning results. On this basis, by performing three independent positioning operations, the random errors and uncertainties that may exist in a single positioning can be effectively reduced. Each independent operation is executed completely from signal acquisition and processing to coordinate calculation, or different processing parameters are used to obtain multiple sets of independent positioning results. These independent results are analyzed, for example, by calculating the spatial deviation between them. If the deviation is lower than the minimum allowable deviation value, the point can be confirmed as a stable defect source. This mechanism of comparison followed by repeated verification significantly improves the accuracy, stability, and reliability of the positioning results, providing a solid foundation for the accurate positioning of weak partial discharges inside the transformer, thereby enabling more accurate identification and confirmation of early insulation defect sources.

[0063] In some of the embodiments described above in this application, a micromechanical vibration-sensitive structure is proposed for detecting vibration amplitude. However, in the implementation process, due to insufficient sensitivity of the detection structure or inaccurate signal conversion, it is difficult to accurately capture weak vibration signals, thereby affecting the reliable output of effective signals.

[0064] In this regard, this application further proposes that the micromechanical vibration sensitive structure in the UHF sensor unit is a microcantilever beam, one end of which is fixed to a silicon substrate, and the other end extends freely and is directly coupled to the radiating element of the UHF antenna. A capacitive displacement detection structure is provided between the bottom of the microcantilever beam and the surface of the silicon substrate to convert the displacement of the microcantilever beam into a voltage signal to characterize the vibration amplitude.

[0065] Specifically, the micromechanical vibration-sensitive structure employs a microcantilever beam design. This microcantilever beam is a miniature mechanical structure, typically made of materials such as silicon or polymers, possessing a high aspect ratio and low stiffness, making it extremely sensitive to minute force or displacement changes. Its function is to act as a vibration-sensitive element, converting the mechanical vibrations caused by weak sound waves or pressure waves generated by partial discharge into measurable mechanical deformation. This microcantilever beam can be manufactured using microelectromechanical systems (MEMS) processes, forming the cantilever beam structure on a silicon wafer through techniques such as photolithography and etching. Alternatively, a piezoelectric material can be used as the main body of the microcantilever beam, utilizing its piezoelectric effect to directly convert mechanical deformation into an electrical signal. One end of the microcantilever beam is fixed to a silicon substrate. The design aims to provide stable mechanical support and a reference benchmark, ensuring that the microcantilever beam deflects in a predictable manner during vibration and preventing unnecessary movement or damage in the complex environment inside the transformer. This fixation can be achieved through eutectic bonding, anodic bonding, or epoxy resin bonding, or by integral molding with a silicon substrate during MEMS manufacturing. The other end of the microcantilever beam extends freely and is directly coupled to the radiating element of the UHF antenna. The purpose is to ensure that the free end of the microcantilever beam responds to vibration to the greatest extent possible and to closely integrate this mechanical response with the function of the UHF antenna, achieving synchronous sensing of vibration and UHF signals, reducing signal transmission loss and time delay. This direct coupling can be achieved through… The free end of the microcantilever beam is physically contacted or connected to the radiating element of the UHF antenna (e.g., a patch of a microstrip antenna or an arm of a dipole antenna) through a very small gap, allowing the vibration of the microcantilever beam to directly affect the geometry of the radiating element or its relative position with the surrounding medium. Alternatively, a microelectrode can be integrated at the free end of the microcantilever beam, forming a variable capacitor with the radiating element of the UHF antenna. The vibration of the microcantilever beam causes a change in capacitance, which in turn affects the resonant frequency or impedance matching of the antenna. Furthermore, a capacitive displacement detection structure is provided between the bottom of the microcantilever beam and the surface of the silicon substrate. Its function is to accurately convert the minute mechanical displacement of the microcantilever beam into a measurable change in capacitance, which is essential for achieving high-sensitivity vibration detection. The key to this measurement is that the structure can fabricate metal electrodes on the bottom of the microcantilever beam and the corresponding surface of the silicon substrate to form a parallel plate capacitor; or it can use a comb-shaped electrode structure, that is, to fabricate staggered finger-shaped electrodes on the bottom of the microcantilever beam and the surface of the substrate. Finally, this structure is used to convert the displacement of the microcantilever beam into a voltage signal to characterize the vibration amplitude, that is, to convert the capacitance change generated by the capacitive displacement detection structure into a standard voltage signal for subsequent signal acquisition, processing and analysis. This can be achieved by a capacitance-to-voltage conversion circuit (such as a charge amplifier, switched capacitor circuit or oscillator circuit), or by using a differential capacitance detection scheme, which improves the detection accuracy by measuring the difference or ratio of two capacitors and converts it into a voltage output.

[0066] Through the above technical solution, the micromechanical vibration sensitive structure is specifically designed as a microcantilever beam, with one end fixed to a silicon substrate and the other end extending freely and directly coupled to the radiating element of the UHF antenna. This application can effectively capture weak mechanical vibrations generated by partial discharge by utilizing the high sensitivity characteristics of the microcantilever beam. At the same time, by setting a capacitive displacement detection structure between the bottom of the microcantilever beam and the surface of the silicon substrate, and converting its displacement into a voltage signal to characterize the vibration amplitude, the precise quantification of weak vibration signals is achieved. This design not only improves the sensitivity and signal-to-noise ratio of vibration detection and solves the problem of insufficient sensitivity of traditional detection structures, but also ensures the synchronous response of the vibration signal and the UHF signal at the physical level through direct coupling, providing a more reliable input for subsequent synchronous detection and positioning. This effectively improves the identification capability and positioning accuracy of weak partial discharge events and avoids the problem of effective signal output being affected by inaccurate signal conversion.

[0067] In some of the embodiments described above in this application, a positioning method based on a UHF sensor is proposed for high-precision positioning of partial discharge. However, in this process, the positioning results may be affected by fluctuations in environmental parameters or lack of historical data verification, resulting in insufficient reliability.

[0068] In response, this application further proposes a discharge state analysis step, which aims to deeply verify and evaluate the partial discharge location information obtained through the positioning method, so as to improve the reliability of the positioning results and the accuracy of the diagnosis. It is not just about simply giving the location, but also about combining multi-dimensional information to make a comprehensive judgment on the rationality, stability and potential risks of the location. This step can be implemented by an independent software module or processing unit, which receives the positioning results and calls other data sources (such as environmental sensor data, historical databases) for analysis; or it can be integrated into the main control unit as a post-processing link in the positioning process, and automatically analyzed through preset logic algorithms and rule engines.

[0069] Specifically, the discharge state analysis step includes acquiring current environmental parameters. Acquiring current environmental parameters refers to real-time monitoring of key physical quantities in the transformer's operating environment. These parameters may affect the occurrence and development of partial discharge or the propagation characteristics of UHF signals. The purpose of acquiring these parameters is to assess whether the current positioning results are obtained under stable and reliable environmental conditions, and to eliminate the interference of environmental factors on positioning accuracy. For example, real-time data can be collected by temperature sensors, humidity sensors, pressure sensors, etc., deployed on or around the transformer body, and the data can be transmitted to the data processing center. Alternatively, operating data such as load current, oil temperature, and winding temperature can be obtained through the transformer's own SCADA (Supervisory and Data Acquisition) system. These data indirectly reflect the transformer's operating status and environmental conditions.

[0070] Simultaneously, this step also acquires the actual defect location and discharge characteristic parameters from the historical discharge record database. The historical discharge record database is a collection of data storing previously confirmed partial discharge defect information. This information includes the precise spatial location of the defect inside the transformer (e.g., confirmed through disassembly inspection or high-precision diagnosis) and the discharge characteristics associated with these defects (such as the spectral characteristics of UHF signals, pulse repetition rate, discharge quantity, etc.). Its function is to provide an empirical reference benchmark for the current location results for comparison and verification. This database can be a structured relational database, storing fields such as defect ID, location coordinates (X, Y, Z), defect type (e.g., winding interlayer discharge, bushing surface discharge), typical UHF spectrum, vibration characteristics, etc.; or it can be an unstructured data lake containing historical reports, images, waveform data, etc., through data mining and pattern recognition techniques to extract key defect location and characteristic information.

[0071] Based on this, the matching degree is calculated between the location results and the historical defect distribution map. The matching degree calculation refers to comparing the partial discharge location obtained by the current location through the UHF sensor unit with the known defect location distribution recorded in the historical database, and quantifying the similarity between the two. The higher the matching degree, the more consistent the current location result is with historical experience, and the higher its reliability. For example, spatial distance calculation methods, such as Euclidean distance and Manhattan distance, can be used to calculate the distance between the current location point and each known defect point in the historical map. The smaller the distance, the higher the matching degree. Alternatively, a region-based or partition-based matching method can be used to divide the inside of the transformer into multiple typical defect areas, determine whether the current location point falls into a certain historically high-incidence defect area, and calculate the matching degree based on the overlap or inclusion relationship of the areas.

[0072] If the matching degree is higher than the preset confidence threshold and the environmental parameters do not fluctuate drastically, the confidence level of the result is increased. The preset confidence threshold is a pre-defined numerical standard used to determine whether the matching degree between the location result and historical maps reaches an acceptable level. Only when the matching degree exceeds this threshold is the current location result considered to have sufficient historical experience support, and its confidence level can be further increased. This threshold can be determined based on historical data analysis, expert experience, or statistical methods. For example, it can be set to 0.8 (representing 80% similarity) or a certain distance value (e.g., the distance between the location point and the nearest historical defect point is less than 5 mm). Alternatively, the threshold can be dynamically adjusted, adaptively adjusting according to factors such as the transformer type, operating years, and importance. "No drastic fluctuations in environmental parameters" refers to the stability of key parameters in the transformer operating environment (such as temperature, humidity, and load) during partial discharge location and analysis. Maintaining a relatively stable range, without any abnormal changes that could affect signal propagation or discharge characteristics, is a crucial prerequisite for ensuring the reliability of the positioning results and avoiding misjudgments in unstable environments. This can be achieved, for example, by setting a threshold for the fluctuation range of environmental parameters. If environmental parameters show an abnormally rapid rise or fall within a short period of time, it is considered that there is a drastic fluctuation. Improving the credibility level of the result means assigning a higher reliability or confidence rating to the current partial discharge positioning result after meeting all verification conditions (high matching degree and stable environment). This helps decision-makers to more accurately judge the severity of the defect and take corresponding maintenance measures. For example, this can be achieved by clearly marking "high credibility positioning result" in the diagnostic report or assigning a numerical credibility score; or, the high credibility result can be automatically pushed to maintenance personnel or a higher-level early warning mechanism can be triggered through the system's internal decision-making logic.

[0073] Through the above technical solution, this application effectively addresses the problem of insufficient reliability in location results. By introducing a multi-dimensional data verification mechanism, including real-time environmental parameter monitoring and historical data comparison, the reliability of the location results is significantly improved. This not only avoids misjudgments caused by environmental fluctuations but also enhances confidence in the determination of defect locations through matching with historical experience. Ultimately, highly reliable location results can provide a more accurate and reliable basis for transformer condition-based maintenance, supporting the transformation from "post-event handling" to "pre-event early warning," thereby effectively reducing the risk of catastrophic failures caused by partial discharge.

[0074] In some of the solutions mentioned above in this application, a positioning method based on UHF sensors is proposed for high-precision positioning of transformer partial discharge. However, in the process of implementing this method, insufficient system integration and modular design may lead to unstable signal acquisition, uncoordinated processing flow, low computational efficiency, or lack of result verification, thereby affecting positioning accuracy and reliability.

[0075] In response, this application proposes a transformer partial discharge location system based on a UHF sensor, which includes a sensor array, a signal processing module, a location calculation module, and a result verification module.

[0076] The sensor array consists of three UHF sensor units integrated with micromechanical vibration-sensitive structures, arranged in an equilateral triangle. This sensor array is the foundation for the system's signal acquisition. Through the collaborative work of multiple sensor units, it can capture UHF electromagnetic signals and mechanical vibration signals generated by partial discharge from different spatial locations. Each UHF sensor unit integrates a micromechanical vibration-sensitive structure and a UHF antenna, enabling it to simultaneously sense two physical phenomena. The micromechanical vibration-sensitive structure can take various forms, such as a microcantilever beam structure, with one end fixed and the other end freely extending, and the vibration amplitude is characterized by detecting its displacement; or it can use micro-diaphragm sensors, piezoelectric thin-film sensors, etc., all of which can convert weak mechanical vibrations into measurable electrical signals. The UHF antenna is responsible for capturing ultra-high frequency electromagnetic waves generated by partial discharge. Its design can use microstrip antennas, dipole antennas, etc., and impedance matching and radiation efficiency in the transformer oil medium environment must be considered. The three sensor units are arranged in an equilateral triangle. This symmetrical geometric configuration helps simplify the subsequent positioning algorithm and reduces geometric errors that may be caused by uneven sensor deployment, ensuring the geometric consistency of signal source location calculation.

[0077] The signal processing module verifies signal synchronization, feature matching, and triggering logic. This module preprocesses, filters, and verifies the raw signals acquired by the sensor array, ensuring that only valid signals meeting specific conditions are used in subsequent positioning calculations. Regarding triggering logic, this module ensures that a valid signal is output only when the micromechanical vibration amplitude and UHF signal strength simultaneously reach their respective preset minimum thresholds. This can be achieved through a hardware logic comparator or by using a software algorithm in the embedded processor to monitor in parallel and perform logical AND operations. For signal synchronization verification, this module determines whether the UHF signal and the micromechanical vibration signal originate from the same discharge event. For example, it can... The high-precision timing circuit determines the time difference between the arrival times of the rising edges of two signals. If the difference is less than or equal to a preset synchronization tolerance threshold, the signal is considered a synchronization signal. Alternatively, the waveform similarity of the two signals can be analyzed using a cross-correlation algorithm, or their phase consistency can be determined through frequency domain analysis. In terms of feature matching verification, this module further confirms whether the signal has typical characteristics of partial discharge. For example, it verifies whether the frequency energy distribution of the UHF signal is within the predetermined discharge characteristic frequency band, and simultaneously verifies whether the time domain or frequency domain characteristics of the micromechanical vibration signal match the predetermined discharge vibration characteristics. Alternatively, a machine learning model can be used to classify the signal and determine whether it belongs to a known discharge type.

[0078] The positioning calculation module calculates coordinates based on time difference and geometric constraints. This module receives valid signals verified by the signal processing module and uses the time information of these signals and the geometric layout of the sensor array to accurately calculate the spatial location of the power source. Specifically, the module uses the time difference of arrival (TDOA) information of the signals received by the three sensor units, combined with the equilateral triangle geometric layout of the sensor array and the known propagation speed of the signal in the medium inside the transformer, to solve for a unique spatial coordinate solution that satisfies all spatiotemporal constraints through triangulation, least squares method or iterative optimization algorithm.

[0079] The result verification module verifies the regional rationality and stability of the positioning results. This module further verifies and filters the spatial coordinates output by the positioning calculation module to improve the reliability and credibility of the positioning results. Regarding regional rationality verification, this module checks whether the positioning results are located in areas with a high incidence of typical defects inside the transformer. For example, it compares the positioning results with a distribution map of typical defects inside the transformer. If the location belongs to a critical area such as between winding layers, the core grounding plate, or the bushing root, it is considered a valid positioning result. Alternatively, it excludes positioning results located outside the transformer or in non-insulated areas through preset geometric boundary conditions. Regarding stability verification, this module evaluates the consistency and repeatability of the positioning results. For example, it performs multiple independent positioning operations on the same suspected defect point. If the spatial deviation of the multiple results is lower than the minimum allowable deviation value, the point is confirmed as a stable defect source. Furthermore, statistical methods, such as calculating the variance or standard deviation of multiple positioning results, can also be used to assess its stability.

[0080] Through the above technical solution, this application provides a transformer partial discharge location system with a clear structure and complete functions. The integrated design and equilateral triangular layout of the sensor array lay the foundation for high-precision signal acquisition, effectively overcoming the limitations of traditional UHF sensors in weak signal detection and spatial deployment. The signal processing module, through a multi-dimensional verification mechanism, including trigger logic, signal synchronization verification, and feature matching verification, can effectively filter out noise and interference, ensuring that only real and valid signals that conform to discharge characteristics enter subsequent processing, significantly improving the purity and reliability of the signal. The location calculation module combines precise time difference measurement and fixed... Geometric constraints can efficiently and accurately solve for the unique spatial coordinates of the discharge source, avoiding multiple ambiguities and improving positioning efficiency. The result verification module further enhances the credibility and practicality of the positioning results through regional rationality and stability checks, ensuring that the positioning results output by the system are not only accurate but also meet actual engineering requirements. Overall, through modular design and collaborative work between modules, the system solves problems that may occur when implementing high-precision partial discharge positioning methods, such as insufficient system integration, uncoordinated signal processing, low computational efficiency, and lack of result verification, thereby significantly improving the accuracy and reliability of transformer partial discharge positioning.

[0081] All content not described in detail in this specification belongs to existing technology known to those skilled in the art, and the model parameters of each electrical appliance are not specifically limited; conventional equipment can be used. Electrical control components not mentioned in this technical solution are not shown in the figures because they belong to existing technology, and will not be described further here. The above embodiments are only used to illustrate the technical solutions of this invention, and not to limit it. Although this invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this invention.

Claims

1. A UHF sensor based transformer partial discharge location method, characterized in that, The method comprises the following steps: Three UHF sensor units in an equilateral triangle layout are arranged in a partial discharge high-occurrence area inside a transformer, each unit is in an equilateral triangle layout and has a three-centimeter adjacent spacing; each UHF sensor unit is integrated with a micro-mechanical vibration sensitive structure and a UHF antenna; When partial discharge occurs, the micro-mechanical vibration amplitude and the UHF signal strength are synchronously detected, and an effective signal is output only when the micro-mechanical vibration amplitude and the UHF signal strength simultaneously trigger the minimum threshold; The arrival time of the three effective signals is combined with the geometric constraint of the equilateral triangle to determine a unique spatial coordinate; Three independent positioning operations are continuously performed on the same suspected defect point, and if the spatial deviations of the three results are all lower than the allowable minimum deviation value, the point is confirmed as a stable defect source.

2. The transformer partial discharge locating method of claim 1, wherein, If the spatial coordinate is located inside the triangle formed by the three UHF sensor units, it is considered as an effective positioning result, and the result is compared with a typical defect distribution map inside the transformer; if the position belongs to the winding interlayer, the core grounding sheet or the sleeve root, the result is reserved, otherwise, no positioning operation is performed.

3. The transformer partial discharge locating method of claim 2, wherein, Before the output of the effective signal, an initial triggering step is further included: the micro-mechanical vibration sensitive structure and the UHF antenna independently collect signals and determine whether the two simultaneously reach the respective preset minimum triggering threshold through a hardware logic comparator.

4. The transformer partial discharge locating method of claim 3, wherein, After the initial triggering step, a signal synchronization verification step is further included: a high-precision timing circuit is used to determine the time difference between the rising edge arrival times of the micro-mechanical vibration signal and the UHF signal; if the time difference is less than or equal to a preset synchronization tolerance threshold, the signals are determined as synchronous signals, and the subsequent positioning step is entered.

5. The transformer partial discharge locating method of claim 4, wherein, After the signal synchronization verification step, a feature matching verification step is further included: for the signals determined as synchronous, it is further verified whether the frequency energy distribution of the UHF signal is within a predetermined discharge characteristic frequency band, and whether the time domain or frequency domain characteristics of the micro-mechanical vibration signal are consistent with the predetermined discharge vibration characteristics.

6. The transformer partial discharge locating method of claim 5, wherein, After the feature matching verification step, a core positioning step is entered: based on the signals of the three UHF sensor units verified, the arrival time difference between each two is calculated, and combined with the geometric constraint of the equilateral triangle layout and the known propagation speed of the signal, a unique spatial coordinate solution satisfying all space-time constraint conditions is solved.

7. The transformer partial discharge locating method of claim 6, wherein, After obtaining the unique spatial coordinate solution, the positioning result is compared, and after the comparison passes, three independent positioning operations are performed to complete accurate positioning.

8. The transformer partial discharge locating method of claim 1, wherein, The micro-mechanical vibration sensitive structure in the UHF sensor unit is a micro-cantilever beam, one end of which is fixed to a silicon substrate, the other end of which freely extends and directly couples with the radiation unit of the UHF antenna, and a capacitive displacement detection structure is arranged between the bottom of the micro-cantilever beam and the surface of the silicon substrate, which is used to convert the displacement of the micro-cantilever beam into a voltage signal to represent the vibration amplitude.

9. The transformer partial discharge locating method of claim 1, wherein, A discharge state analysis step is further included: the current environmental parameters and the real defect positions and discharge characteristic parameters in the historical discharge record database are obtained. The positioning result is matched with a historical defect distribution atlas to calculate a matching degree, and if the matching degree is higher than a preset threshold and the environmental parameters have no dramatic fluctuation, the credibility level of the result is improved.

10. A UHF sensor based transformer partial discharge positioning system for implementing the transformer partial discharge positioning method of claims 1-9, characterized by, It comprises: a sensor array composed of three UHF sensor units integrating micro-mechanical vibration sensitive structures, arranged in an equilateral triangle; a signal processing module for verifying signal synchronization, feature matching and trigger logic; a positioning calculation module for calculating coordinates based on time difference and geometric constraints; a result verification module for checking the positioning result for regional rationality and stability.

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