Transformer partial discharge source space positioning system and method

Abstract

The invention discloses a spatial positioning system and method for a partial discharge source of a transformer, and the system can accurately calculate the three-dimensional coordinates of the partial discharge source through the spatial layout and phase difference measurement of multiple sensors in combination with a geometric calculation method. Aiming at complex electromagnetic interference in the operation environment of the transformer, a dynamic phase difference compensation algorithm is adopted, and the electromagnetic interference is adaptively suppressed by analyzing the phase difference of signals received by each sensor, so that accurate extraction of partial discharge signals is ensured; the compensation algorithm can be automatically adjusted according to the change of the interference intensity, and the robustness of the system is effectively improved; according to the invention, through the adaptive weighting function, the partial discharge signal and the environmental noise signal can be effectively distinguished, and accurate processing of the signal is ensured; particularly, through dynamic adjustment of the exponential attenuation function and the noise power spectrum density, the influence of interference signals can be further weakened, and the signal processing precision is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of local discharge source positioning, and in particular to a system and method for spatially positioning a local discharge source of a transformer. Background Art

[0002] Partial discharge is one of the common fault precursors of power equipment, such as transformers, during operation. Partial discharge will cause the insulation medium to gradually deteriorate, eventually leading to insulation breakdown, affecting the operational safety of the transformer. For this reason, partial discharge monitoring and positioning technology plays an important role in transformer fault diagnosis and preventive maintenance. Existing partial discharge monitoring technologies include ultrasonic, pulse current and electromagnetic wave methods, which can effectively detect partial discharge signals. However, most of these technologies are limited to the analysis of a single signal source, and have poor suppression effects on electromagnetic interference signals, especially in complex electromagnetic environments. It is easy to misjudge or miss partial discharge signals, making it difficult to achieve accurate three-dimensional positioning.

[0003] The existing technologies mainly rely on the difference in signal arrival time (TDOA) or signal phase difference (Phase Difference) in locating the local discharge source. However, these methods are limited by factors such as the arrangement of the sensor array, synchronization errors, and electromagnetic interference, resulting in low positioning accuracy. Especially in the actual working environment of the transformer, the electromagnetic interference and noise are complex and changeable. The existing technologies cannot dynamically and adaptively handle these interferences, making it difficult to achieve high-precision local discharge source positioning. Summary of the invention

[0004] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0005] Therefore, in order to solve the above technical problems, the present invention provides the following technical solutions: a transformer partial discharge source spatial positioning system, comprising a signal acquisition module, an electromagnetic interference dynamic suppression module, a signal processing module and a three-dimensional positioning module;

[0006] The signal acquisition module is used to simultaneously receive the signal from the local discharge source and the electromagnetic interference signal generated by the operation of the transformer;

[0007] The electromagnetic interference dynamic suppression module is used to analyze the phase difference of the received signal, dynamically adjust the phase of the signal, and eliminate electromagnetic interference in real time;

[0008] Signal processing module, used to optimize the collected signals, ensure that the partial discharge signals are accurately extracted and effectively distinguished from the interference signals in the environment;

[0009] The three-dimensional positioning module is used to perform high-precision three-dimensional positioning through the spatial layout of multiple sensors combined with phase difference measurement technology, thereby determining the specific location of the local discharge source.

[0010] As a preferred solution of the transformer partial discharge source spatial positioning system of the present invention, the signal acquisition module includes sensors and multi-channel high-speed data collectors, which are arranged in arrays at different positions around the transformer to form a spatial three-dimensional network, thereby ensuring effective spatial positioning of the transformer partial discharge source in the later stage.

[0011] As a preferred solution of the transformer local discharge source spatial positioning system described in the present invention, the electromagnetic interference dynamic suppression module includes an interference signal identification unit and a dynamic phase difference compensation unit; wherein the interference signal identification unit, by utilizing signals received by multiple sensors and analyzing the phase difference of signals received by each sensor, identifies common-mode signals caused by electromagnetic interference, and these signals usually have strong phase consistency or specific phase relationship; the dynamic phase difference compensation unit is used to calculate the phase difference between signals received by different sensors through a dynamic phase difference compensation algorithm, adjust the phase of the signal, thereby effectively eliminating the influence of electromagnetic interference in the signal processing process, and the dynamic phase difference compensation algorithm is adaptively adjusted according to changes in the environment and equipment operating conditions.

[0012] As a preferred solution of the transformer partial discharge source spatial positioning system of the present invention, the calculation method of the dynamic phase difference compensation algorithm is as follows:

[0013] First, define the key variables used in the formula:

[0014] S i (t): the original signal received by the i-th sensor at time t;

[0015] φ i (t): the phase of the signal received by the i-th sensor;

[0016] Δφ i,j (t) = φ i (t)-φ j (t): phase difference between the i-th and j-th sensors;

[0017] D(t): estimated value of the interference signal, which depends on the phase difference of the signals received by multiple sensors;

[0018] ω(t): time-dependent adaptive weight function used to adjust the signal compensation process;

[0019] P(t): partial discharge signal after compensation;

[0020] The dynamic phase difference compensation formula is as follows:

[0021]

[0022] Among them, signal compensation: The signal S of each sensor in the formula i (t) are all compensated, and the compensation amount is based on the phase difference Δφ i,j (t) is controlled by a dynamic adaptive function, and the phase difference reflects the degree of electromagnetic interference of signals received by different sensors;

[0023] Exponential decay function: To measure the impact of electromagnetic interference, an exponential decay function is used. As the phase difference increases, the impact of interference is further weakened;

[0024] Integral Item: Integrate the interference signal to calculate the cumulative interference; this can help accurately estimate the impact of the interference signal and compensate for the interference in the time domain;

[0025] Adaptive weight function ω(t): This weight function is used to dynamically adjust the compensation process to ensure that the algorithm can adaptively optimize the compensation strength of interference according to changes in time and environment. This adaptive mechanism ensures the robustness of the algorithm and can dynamically adapt to changes in transformer load and electromagnetic environment.

[0026] Overall compensation mechanism: At the end of the formula, the signals of all sensors are summed and divided by the number of sensors N to achieve global dynamic compensation and reconstruction of the signal;

[0027] The value range of P(t) is the partial discharge signal after compensation, which is a time-varying signal. Since the formula contains exponential function, integral and adaptively adjusted weight function, P(t) should tend to the net value of the partial discharge signal after compensation, and the interference component will be greatly weakened.

[0028] As a preferred solution of the transformer partial discharge source spatial positioning system of the present invention, the calculation formula of the adaptive weight function ω(t) is as follows:

[0029]

[0030] Among them, σ s (t): standard deviation of the sensor real-time signal S(t), representing the amplitude of signal fluctuation; a larger standard deviation usually indicates stronger interference in the signal, so the compensation strength can be dynamically adjusted by controlling the value of ω(t) by the standard deviation; α is the adjustment coefficient related to the signal strength;

[0031] The time derivative of the signal standard deviation indicates the change in the fluctuation rate of the signal, reflecting the speed of change of the interference intensity. If the noise intensity changes drastically, the speed of compensation adjustment needs to be accelerated, so this item is used to control the dynamic response of the compensation. The coefficient β is used to control the impact of this item on the compensation.

[0032] P noise (t): The noise power spectral density (PSD) measured in real time, which is an indicator of noise intensity;

[0033] α, β, γ: weight adjustment coefficients, used to balance the impact of different factors, and need to be adjusted according to actual application conditions;

[0034] In this formula, the cumulative noise power spectral density This integral term reflects the cumulative intensity of the total noise. As time goes by, the cumulative effect of the noise will become more and more obvious, prompting the system to make more adaptive compensation adjustments. The coefficient γ is used to adjust the impact of noise accumulation on the weight.

[0035] The inverse form of the overall formula: This design ensures that when the noise intensity or signal fluctuation is large, the weight value ω(t) will decrease, thereby increasing the compensation strength; when the signal is stable or the noise is small, the weight value will increase, reducing the compensation strength and avoiding over-compensation.

[0036] As a preferred solution of the transformer partial discharge source spatial positioning system described in the present invention, the step of adaptively optimizing the compensation strength is as follows: when the signal interference is enhanced, the system adaptively reduces ω(t) to enhance the compensation effect; conversely, when the interference is small or the environment is stable, the system adaptively increases ω(t) to reduce the compensation strength and avoid over-compensation.

[0037] As a preferred solution of the transformer partial discharge source spatial positioning system described in the present invention, the signal processing module includes a filter and a signal denoising and enhancement unit; wherein the filter is used to filter out most of the low-frequency noise and other background interference signals to ensure accurate extraction of the partial discharge signal; the signal denoising and enhancement unit is used to extract the characteristics of the partial discharge signal, and effectively distinguish the partial discharge signal from other interference signals through signal feature extraction.

[0038] As a preferred solution of the transformer local discharge source spatial positioning system of the present invention, the three-dimensional positioning module constructs a three-dimensional spatial positioning model, combines the multi-sensor array arrangement and phase difference measurement, and uses a geometric solution method to solve the three-dimensional spatial coordinates of the local discharge source to determine the specific position (x0, y0, z0) of the local discharge source inside the transformer.

[0039] The present invention also provides the above-mentioned method for spatially locating the local discharge source of the transformer, which comprises the following specific steps:

[0040] S1: multiple sensors are arranged around the transformer to collect internal signals of the transformer, including partial discharge signals and electromagnetic interference signals generated during operation; the multiple sensors are evenly distributed in a three-dimensional array outside the transformer to ensure that the sensors cover the signals of the discharge source in space;

[0041] S2: When the local discharge source generates an electromagnetic signal, the sensor array will receive the signal simultaneously. Each sensor i Record the signal S at all times i (t) (the signal is the original signal, including the local discharge signal and the environmental noise interference), and generates the corresponding electromagnetic wave data;

[0042] S3: Use a high-precision clock synchronization device, such as GPS or an internal high-precision clock module, to ensure that all sensors are sampled on the same time basis (the synchronization error should be controlled at the nanosecond level to avoid affecting the accuracy of the phase difference calculation);

[0043] S4: In the received signal, the local discharge signal and the environmental noise signal are distinguished by the adaptive weight function ω(t);

[0044] S5: Filter out most of the low-frequency noise and other background interference signals through the filter, extract the characteristics of the partial discharge signal, and effectively distinguish the partial discharge signal from other interference signals;

[0045] S6: For any two sensors i and j, the phase difference Δφ of the received signals is calculated by the formula i,j (t); through the dynamic phase difference compensation formula P(t), the interference is compensated and the effective partial discharge signal P(t) is extracted to locate the discharge source;

[0046] S7: Signal arrival time t recorded by each sensor i and the spatial position of each sensor, combined with the electromagnetic wave propagation speed c, to construct a three-dimensional spatial positioning model;

[0047] S8: The three-dimensional coordinates of the local discharge source are calculated by a geometric solution method to achieve spatial positioning of the local discharge source.

[0048] As a preferred solution of the method for spatially locating the partial discharge source of a transformer according to the present invention, the method comprises: utilizing the time difference between the known spatial position of the sensor array and the propagation of the partial discharge signal to construct a nonlinear equation group, and determining the three-dimensional coordinates (x0, y0, z0) of the discharge source by solving the equation group;

[0049] Assume that there are N sensors, whose spatial positions are known, namely (x i ,y i , z i ), where i = 1, 2, 3, ... N, the three-dimensional coordinates of the discharge source are set to (x0, y0, z0), which is the target to be solved;

[0050] The distance that the signal propagates from the discharge source to the i-th sensor is:

[0051] According to the propagation speed c of electromagnetic waves, the signal propagation time is:

[0052] The actual measured time difference Δt i =t i -t1

[0053] Geometric model based on time difference:

[0054] Select the first (x1, y1, z1) sensor as the reference point and use the time difference with other sensors to construct the geometric solution equation; for each sensor i, we can get the following equation;

[0055]

[0056] The core of the above equations is that the distance difference between the two sensors and the discharge source is proportional to the time difference;

[0057] The time difference Δt across all sensors i Construct N-1 equations, and finally form a nonlinear equation system:

[0058]

[0059] The form of the equation group is nonlinear. After solving it by the least square method or nonlinear optimization (such as Newton's method), (x0, y0, z0) can be determined to realize the three-dimensional spatial positioning of the local discharge source.

[0060] Beneficial effects of the present invention:

[0061] 1. The present invention can accurately calculate the three-dimensional coordinates of the local discharge source through the spatial layout of multiple sensors and phase difference measurement, combined with a geometric solution method, thus solving the problem of low positioning accuracy in the prior art.

[0062] 2. In view of the complex electromagnetic interference in the transformer operating environment, the present invention adopts a dynamic phase difference compensation algorithm to adaptively suppress electromagnetic interference by analyzing the phase difference of the signals received by each sensor, thereby ensuring the accurate extraction of partial discharge signals. Unlike traditional fixed filters, the compensation algorithm of the present invention can automatically adjust according to the changes in interference intensity, effectively improving the robustness of the system.

[0063] 3. The existing technology is difficult to deal with complex electromagnetic interference, but the present invention can effectively distinguish partial discharge signals from environmental noise signals through adaptive weight functions to ensure accurate signal processing. In particular, through the dynamic adjustment of the exponential decay function and the noise power spectrum density, the influence of interference signals can be further weakened and the accuracy of signal processing can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0065] Figure 1 This is a system architecture diagram of the present invention.

[0066] Figure 2 It is the work flow chart of the present invention. DETAILED DESCRIPTION

[0067] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0068] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0069] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0070] Example 1

[0071] Reference Figures 1-2, which is the first embodiment of the present invention, provides a transformer partial discharge source spatial positioning system, including a signal acquisition module, an electromagnetic interference dynamic suppression module, a signal processing module and a three-dimensional positioning module;

[0072] Among them, the signal acquisition module is used to simultaneously receive signals from the local discharge source and the electromagnetic interference signal generated by the operation of the transformer; specifically, the signal acquisition module includes sensors and multi-channel high-speed data collectors, which are arranged in arrays at different positions around the transformer to form a three-dimensional spatial network, ensuring effective spatial positioning of the local discharge source of the transformer in the later stage.

[0073] The electromagnetic interference dynamic suppression module is used to analyze the phase difference of the received signal, dynamically adjust the phase of the signal, and eliminate the electromagnetic interference in real time; specifically, the electromagnetic interference dynamic suppression module includes an interference signal identification unit and a dynamic phase difference compensation unit;

[0074] Among them, the interference signal identification unit, by using the signals received by multiple sensors and analyzing the phase difference of the signals received by each sensor, identifies the common mode signals caused by electromagnetic interference. These signals usually have strong phase consistency or a specific phase relationship; the dynamic phase difference compensation unit is used to calculate the phase difference between the signals received by different sensors through a dynamic phase difference compensation algorithm, adjust the phase of the signal, and thus effectively eliminate the influence of electromagnetic interference in the signal processing process. The dynamic phase difference compensation algorithm is adaptively adjusted according to changes in the environment and equipment operating conditions;

[0075] The calculation method of the dynamic phase difference compensation algorithm is as follows:

[0076] First, define the key variables used in the formula:

[0077] S i (t): the original signal received by the i-th sensor at time t;

[0078] φ i (t): the phase of the signal received by the i-th sensor;

[0079] Δφ i,j (t) = φ i (t)-φ j (t): phase difference between the i-th and j-th sensors;

[0080] D(t): estimated value of the interference signal, which depends on the phase difference of the signals received by multiple sensors;

[0081] ω(t): time-dependent adaptive weight function used to adjust the signal compensation process;

[0082] P(t): partial discharge signal after compensation;

[0083] The dynamic phase difference compensation formula is as follows:

[0084]

[0085] Among them, signal compensation: The signal S of each sensor in the formula i (t) are all compensated, and the compensation amount is based on the phase difference Δφ i,j (t) is controlled by a dynamic adaptive function, and the phase difference reflects the degree of electromagnetic interference of signals received by different sensors;

[0086] Exponential decay function: To measure the impact of electromagnetic interference, an exponential decay function is used. As the phase difference increases, the impact of interference is further weakened;

[0087] Integral Item: Integrate the interference signal to calculate the cumulative interference; this can help accurately estimate the impact of the interference signal and compensate for the interference in the time domain;

[0088] Adaptive weight function ω(t): This weight function is used to dynamically adjust the compensation process to ensure that the algorithm can adaptively optimize the compensation strength of interference according to changes in time and environment. This adaptive mechanism ensures the robustness of the algorithm and can dynamically adapt to changes in transformer load and electromagnetic environment.

[0089] Overall compensation mechanism: At the end of the formula, the signals of all sensors are summed and divided by the number of sensors N to achieve global dynamic compensation and reconstruction of the signal;

[0090] The value range of P(t) is the partial discharge signal after compensation, which is a time-varying signal. Since the formula contains exponential function, integral and adaptively adjusted weight function, P(t) should tend to the net value of the partial discharge signal after compensation, and the interference component will be greatly weakened.

[0091] As a preferred solution of the transformer partial discharge source spatial positioning system and method described in the present invention, the calculation formula of the adaptive weight function ω(t) is as follows:

[0092]

[0093] Among them, σ s (t): standard deviation of the sensor real-time signal S(t), representing the amplitude of signal fluctuation; a larger standard deviation usually indicates stronger interference in the signal, so the compensation strength can be dynamically adjusted by controlling the value of ω(t) by the standard deviation; α is the adjustment coefficient related to the signal strength;

[0094] The time derivative of the signal standard deviation indicates the change in the fluctuation rate of the signal, reflecting the speed of change of the interference intensity. If the noise intensity changes drastically, the speed of compensation adjustment needs to be accelerated, so this item is used to control the dynamic response of the compensation. The coefficient β is used to control the impact of this item on the compensation.

[0095] P noise (t): The noise power spectral density (PSD) measured in real time, which is an indicator of noise intensity;

[0096] α, β, γ: weight adjustment coefficients, used to balance the impact of different factors, and need to be adjusted according to actual application conditions;

[0097] In this formula, the cumulative noise power spectral density This integral term reflects the cumulative intensity of the total noise. As time goes by, the cumulative effect of the noise will become more and more obvious, prompting the system to make more adaptive compensation adjustments. The coefficient γ is used to adjust the impact of noise accumulation on the weight.

[0098] The inverse form of the overall formula: This design ensures that when the noise intensity or signal fluctuation is large, the weight value ω(t) will decrease, thereby increasing the compensation strength; when the signal is stable or the noise is small, the weight value will increase, reducing the compensation strength and avoiding over-compensation.

[0099] The steps of adaptively optimizing the compensation strength are as follows: when the signal interference increases, the system adaptively reduces ω(t) to enhance the compensation effect; conversely, when the interference is small or the environment is stable, the system adaptively increases ω(t) to reduce the compensation strength and avoid over-compensation.

[0100] The signal processing module is used to optimize the collected signal to ensure that the local discharge signal is accurately extracted and effectively distinguished from the interference signal in the environment; specifically, the signal processing module includes a filter, a signal denoising and enhancement unit; wherein the filter is used to filter out most of the low-frequency noise and other background interference signals to ensure the accurate extraction of the local discharge signal; the signal denoising and enhancement unit is used to extract the characteristics of the local discharge signal, and effectively distinguish the local discharge signal from other interference signals through the signal feature extraction.

[0101] The three-dimensional positioning module is used to perform high-precision three-dimensional positioning through the spatial layout of multiple sensors combined with phase difference measurement technology, so as to determine the specific position of the local discharge source; specifically, the three-dimensional positioning module constructs a three-dimensional spatial positioning model, combines the multi-sensor array layout and phase difference measurement, and uses a geometric solution method to solve the three-dimensional spatial coordinates of the local discharge source to determine the specific position (x0, y0, z0) of the local discharge source inside the transformer.

[0102] The present invention also provides a method for spatially locating a local discharge source of a transformer, comprising the following specific steps:

[0103] S1: multiple sensors are arranged around the transformer to collect internal signals of the transformer, including partial discharge signals and electromagnetic interference signals generated during operation; the multiple sensors are evenly distributed in a three-dimensional array outside the transformer to ensure that the sensors cover the signals of the discharge source in space;

[0104] S2: When the local discharge source generates an electromagnetic signal, the sensor array will receive the signal simultaneously. Each sensor i Record the signal S at all times i (t) (the signal is the original signal, including the local discharge signal and the environmental noise interference), and generates the corresponding electromagnetic wave data;

[0105] S3: Use a high-precision clock synchronization device, such as GPS or an internal high-precision clock module, to ensure that all sensors are sampled on the same time basis (the synchronization error should be controlled at the nanosecond level to avoid affecting the accuracy of the phase difference calculation);

[0106] S4: In the received signal, the local discharge signal and the environmental noise signal are distinguished by the adaptive weight function ω(t);

[0107] S5: Filter out most of the low-frequency noise and other background interference signals through the filter, extract the characteristics of the partial discharge signal, and effectively distinguish the partial discharge signal from other interference signals;

[0108] S6: For any two sensors i and j, the phase difference Δφ of the received signals is calculated by the formula i,j (t); through the dynamic phase difference compensation formula P(t), the interference is compensated and the effective partial discharge signal P(t) is extracted to locate the discharge source;

[0109] S7: Signal arrival time t recorded by each sensor i and the spatial position of each sensor, combined with the electromagnetic wave propagation speed c, to construct a three-dimensional spatial positioning model;

[0110] S8: The three-dimensional coordinates of the local discharge source are calculated by a geometric solution method to achieve spatial positioning of the local discharge source.

[0111] Using the known spatial position of the sensor array and the time difference between the propagation of the partial discharge signal, a nonlinear equation system is constructed and the three-dimensional coordinates (x0, y0, z0) of the discharge source are determined by solving them.

[0112] Assume that there are N sensors, whose spatial positions are known, namely (x i ,yi , z i ), where i = 1, 2, 3, ... N, the three-dimensional coordinates of the discharge source are set to (x0, y0, z0), which is the target to be solved;

[0113] The distance that the signal propagates from the discharge source to the i-th sensor is:

[0114] According to the propagation speed c of electromagnetic waves, the signal propagation time (the time it takes for the signal to reach the i-th sensor) is:

[0115] The actual measured time difference Δt i =t i -t1

[0116] Geometric model based on time difference:

[0117] Select the first (x1, y1, z1) sensor as the reference point and use the time difference with other sensors to construct the geometric solution equation; for each sensor i, we can get the following equation;

[0118]

[0119] The core of the above equations is that the distance difference between the two sensors and the discharge source is proportional to the time difference;

[0120] The time difference Δt across all sensors i Construct N-1 equations, and finally form a nonlinear equation system:

[0121]

[0122] The form of the equation group is nonlinear. After solving it by the least square method or nonlinear optimization, (x0, y0, z0) can be determined to realize the three-dimensional spatial positioning of the local discharge source;

[0123] Specifically, the solution steps are as follows:

[0124] Choose an initial value As an initial estimate of the discharge source;

[0125] For each sensor, calculate the current estimated position The propagation time and the measured time difference Δt i (Δt i =t i -t1) to obtain the error:

[0126]

[0127] Accumulate the errors of all sensors:

[0128]

[0129] Iterative Optimization:

[0130] Update the estimate of (x0, y0, z0) using a numerical method that minimizes the error E;

[0131] The iteration is performed until the error E is smaller than a preset threshold.

[0132] The specific location of the power supply is:

[0133] When the iterative process converges, the estimated position (x0, y0, z0) of the local discharge source is finally obtained.

[0134] Based on the existing partial discharge monitoring technology, the present invention proposes a highly innovative and practical three-dimensional spatial positioning system and method, which can realize high-precision positioning of the transformer partial discharge source. Its combination of dynamic phase difference compensation, adaptive electromagnetic interference suppression and geometric solution method overcomes the shortcomings of the existing technology, can effectively improve the detection accuracy of partial discharge in actual transformer monitoring, and has broad application prospects.

[0135] Example 2

[0136] This is the second embodiment of the present invention. This embodiment is different from the first embodiment in that in order to verify the beneficial effects of the present invention, experimental comparison data between the present invention and the prior art are provided.

[0137] In order to verify the effectiveness of the 3D spatial positioning system for partial discharge sources, this experiment simulates the partial discharge phenomenon inside the transformer and uses a multi-sensor array and phase difference measurement technology to locate the partial discharge source. The experimental platform includes a transformer model, a partial discharge source, a sensor array, a high-speed data acquisition system, a dynamic phase difference compensation module, and a 3D positioning calculation unit. In the experiment, by adjusting the position of the partial discharge source and collecting the signal phase difference of each sensor, the 3D coordinates of the discharge source are finally calculated using a geometric solution method.

[0138] Multi-sensor array arrangement: Eight sensors are arranged around the transformer model to form a three-dimensional sensor array. The specific arrangement positions of the sensors are evenly distributed around the transformer housing, located at the four corners and the middle of the transformer, forming a three-dimensional coordinate system. The spatial position of each sensor is known and represented by the coordinates (x, y, z).

[0139] Signal acquisition and time synchronization: A multi-channel high-speed data acquisition system is used to synchronously collect the signals received by each sensor. In order to ensure the time accuracy of signal acquisition, a nanosecond-level GPS clock synchronization module is used to ensure that all sensors are sampled under the same time reference, and the time synchronization error is controlled within 0.5 nanoseconds.

[0140] Interference signal identification and dynamic phase difference compensation: Due to the electromagnetic noise interference in the environment, the system first uses the electromagnetic interference dynamic suppression module to identify and filter out interference signals through the phase difference of signals received by multiple sensors. The dynamic phase difference compensation algorithm is used to compensate for the signals of each sensor to ensure that the extracted partial discharge signal is clean and effective.

[0141] Partial discharge signal extraction: The system uses a signal processing module, combined with filters and signal enhancement technology, to accurately extract partial discharge signals. The adaptive optimization algorithm automatically adjusts the compensation intensity when the electromagnetic environment changes, making the extracted signal more stable and removing the influence of background noise.

[0142] Construction of three-dimensional spatial positioning model: based on the signal arrival time Δt recorded by each sensor i and the known spatial position of the sensor (x i ,y i , z i ), combined with the propagation speed c of electromagnetic waves in the air, a set of geometric solution equations is established. Through the time difference of multiple sensors and the geometric solution method, the position of the local discharge source is optimized using the least squares method, and the three-dimensional spatial coordinates of the discharge source are finally solved.

[0143] The specific experimental results are shown in the following table:

[0144]

[0145]

[0146] From the table, we can see that there are slight differences in the arrival time of the signals recorded by each sensor. These time differences reflect the distance differences of the electromagnetic waves from the local discharge source to different sensors. Through the geometric solution method, combined with the spatial position of the sensor and the signal arrival time, an accurate three-dimensional positioning model can be constructed. In this experiment, the least squares method was used to solve the equations, and the three-dimensional coordinates of the local discharge source were finally calculated to be (0.75, 0.75, 0.75), with an error of only 0.05 meters from the actual discharge source location.

[0147] By comparing the experimental data of the present invention with that of the conventional technology, it can be seen that the advantages of the present invention are as follows:

[0148] High-precision time synchronization and dynamic compensation: The traditional local discharge source location system has deficiencies in time synchronization error and signal interference compensation, while the present invention significantly improves the accuracy of signal extraction and the accuracy of discharge source location through nanosecond-level time synchronization and dynamic phase difference compensation algorithms. According to experimental data, the signal strength in the traditional method fluctuates greatly, but after dynamic compensation in the present invention, the signal strength is more stable and the noise impact is significantly reduced.

[0149] Optimization of geometric solution method: Compared with the rough processing of three-dimensional positioning of discharge sources in the prior art, the present invention realizes high-precision geometric solution through the least square method and multiple iterative optimization. The positioning error is reduced from the traditional 0.1 meter to 0.05 meter, and the accuracy is improved by 50%.

[0150] Improved anti-interference capability: In an environment with complex electromagnetic interference, traditional positioning methods are often unable to accurately extract local discharge signals. The present invention effectively filters electromagnetic interference signals through adaptive weight functions and dynamic phase difference compensation, making the net value of the extracted local discharge signal higher, thereby improving the robustness of positioning.

[0151] In summary, experiments have verified the significant advantages of the present invention in high-precision three-dimensional positioning. Compared with the existing technology, the present invention not only excels in anti-interference ability, but also reaches a new height in positioning accuracy, and has important application value.

[0152] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A transformer partial discharge source spatial positioning system, characterized in that: It includes a signal acquisition module, an electromagnetic interference dynamic suppression module, a signal processing module and a three-dimensional positioning module; The signal acquisition module is used to simultaneously receive the signal from the local discharge source and the electromagnetic interference signal generated by the operation of the transformer; The electromagnetic interference dynamic suppression module is used to analyze the phase difference of the received signal, dynamically adjust the phase of the signal, and eliminate electromagnetic interference in real time; Signal processing module, used to optimize the collected signals, ensure that the partial discharge signals are accurately extracted and effectively distinguished from the interference signals in the environment; The three-dimensional positioning module is used to perform high-precision three-dimensional positioning through the spatial layout of multiple sensors combined with phase difference measurement technology, thereby determining the specific location of the local discharge source.

2. The transformer partial discharge source spatial positioning system according to claim 1, characterized in that: The signal acquisition module includes sensors, which are arranged in arrays at different positions around the transformer to form a three-dimensional spatial network, thereby ensuring effective spatial positioning of the transformer local discharge source in the later stage.

3. The transformer partial discharge source spatial positioning system according to claim 2, characterized in that: The electromagnetic interference dynamic suppression module includes an interference signal identification unit and a dynamic phase difference compensation unit; wherein the interference signal identification unit identifies the common mode signal caused by electromagnetic interference by utilizing the signals received by multiple sensors and analyzing the phase difference of the signals received by each sensor; the dynamic phase difference compensation unit is used to calculate the phase difference between the signals received by different sensors through a dynamic phase difference compensation algorithm, adjust the phase of the signal, thereby effectively eliminating the influence of electromagnetic interference during the signal processing process, and the dynamic phase difference compensation algorithm is adaptively adjusted according to changes in the environment and equipment operating conditions.

4. The transformer partial discharge source spatial positioning system according to claim 3, characterized in that: The calculation method of the dynamic phase difference compensation algorithm is as follows: First, define the key variables used in the formula: S i (t): the original signal received by the i-th sensor at time t; φ i (t): the phase of the signal received by the i-th sensor; Δφ i,j (t) = φ i (t)-φ j (t): phase difference between the i-th and j-th sensors; D(t): estimated value of interference signal, which depends on the phase difference of signals received by multiple sensors; ω(t): time-dependent adaptive weight function used to adjust the signal compensation process; P(t): compensated partial discharge signal; The dynamic phase difference compensation formula is as follows: Among them, signal compensation: The signal S of each sensor in the formula i (t) are all compensated, and the compensation amount is based on the phase difference Δφ i,j (t) is controlled by a dynamic adaptive function, and the phase difference reflects the degree of electromagnetic interference of signals received by different sensors; Exponential decay function: To measure the impact of electromagnetic interference, an exponential decay function is used. As the phase difference increases, the impact of interference is further weakened; Integral Item: Integrate the interference signal to calculate the cumulative interference, help accurately estimate the impact of the interference signal, and compensate for the interference in the time domain; Adaptive weight function ω(t): This weight function is used to dynamically adjust the compensation process to ensure that the algorithm adaptively optimizes the compensation strength of interference according to changes in time and environment. This adaptive mechanism ensures the robustness of the algorithm and enables it to dynamically adapt to changes in transformer load and electromagnetic environment; Overall compensation mechanism: This formula achieves global dynamic compensation and reconstruction of the signal by summing up the signals of all sensors and dividing by the number of sensors N; The value range of the formula P(t) is the compensated partial discharge signal. Since the formula contains an exponential function, an integral, and an adaptively adjusted weight function, P(t) tends to the net value of the partial discharge signal after compensation, and the interference component is greatly weakened.

5. The transformer partial discharge source spatial positioning system according to claim 4, characterized in that: The calculation formula of the adaptive weight function ω(t) is as follows: Among them, α, β, γ are weight adjustment coefficients, which are used to balance the influence of different factors and are adjusted according to the actual application situation; σ s (t): standard deviation of the real-time sensor signal S(t), representing the amplitude of signal fluctuation; a larger standard deviation indicates that the interference in the signal is stronger. The value of ω(t) is controlled by the standard deviation to dynamically adjust the compensation intensity; The time derivative of the signal standard deviation indicates the change in the fluctuation rate of the signal, reflecting the speed of change in the interference intensity. If the noise intensity changes dramatically, the speed of compensation adjustment will be accelerated, thereby achieving a dynamic response of compensation. P noise (t): noise power spectrum density measured in real time, which is used as an indicator to measure the noise intensity; In this formula, the cumulative noise power spectral density The integral term reflects the cumulative intensity of the total noise. As time goes by, the cumulative effect of the noise becomes more and more obvious, prompting the system to make more adaptive compensation adjustments.

6. The transformer partial discharge source spatial positioning system according to claim 5, characterized in that: The steps of adaptively optimizing the compensation strength are as follows: when the signal interference increases, the system adaptively reduces ω(t) to enhance the compensation effect; conversely, when the interference is small or the environment is stable, the system adaptively increases ω(t) to reduce the compensation strength and avoid over-compensation.

7. The transformer partial discharge source spatial positioning system according to claim 6, characterized in that: The signal processing module includes a filter, a signal denoising and enhancement unit; wherein the filter is used to filter out most of the low-frequency noise and other background interference signals to ensure accurate extraction of the local discharge signal; the signal denoising and enhancement unit is used to extract the characteristics of the local discharge signal, and effectively distinguish the local discharge signal from other interference signals through signal feature extraction.

8. The transformer partial discharge source spatial positioning system according to claim 7, characterized in that: The three-dimensional positioning module constructs a three-dimensional spatial positioning model, combines multi-sensor array arrangement and phase difference measurement, and uses a geometric solution method to solve the three-dimensional spatial coordinates of the local discharge source to determine the specific position of the local discharge source inside the transformer.

9. The method for spatially locating a transformer partial discharge source according to claim 8, characterized in that: The specific steps include: S1: multiple sensors are arranged around the transformer to collect internal signals of the transformer, including partial discharge signals and electromagnetic interference signals generated during operation; the multiple sensors are evenly distributed in a three-dimensional array outside the transformer to ensure that the sensors cover the signals of the discharge source in space; S2: When the local discharge source generates an electromagnetic signal, the sensor array receives the signal at the same time, and each sensor receives the signal at time t i Record the signal S at all times i (t), and generate corresponding electromagnetic wave data; S3: Use a high-precision clock synchronization device to ensure that all sensors are sampled on the same time basis; S4: In the received signal, the local discharge signal and the environmental noise signal are distinguished by the adaptive weight function ω(t); S5: Filter out most of the low-frequency noise and other background interference signals through the filter, extract the characteristics of the partial discharge signal, and effectively distinguish the partial discharge signal from other interference signals; S6: For any two sensors i and j, the phase difference Δφ of the received signals is calculated by the formula i,j (t); The interference is compensated by the dynamic phase difference compensation formula P(t), and the effective partial discharge signal P(t) is extracted to locate the discharge source. S7: Signal arrival time t recorded by each sensor i and the spatial position of each sensor, combined with the electromagnetic wave propagation speed c, to construct a three-dimensional spatial positioning model; S8: The three-dimensional coordinates of the local discharge source are calculated by a geometric solution method to achieve spatial positioning of the local discharge source.

10. The transformer partial discharge source spatial positioning system according to claim 9, characterized in that: The specific geometric solution method is as follows: using the known spatial position of the sensor array and the time difference between the propagation of the partial discharge signal, a nonlinear equation system is constructed, and the three-dimensional coordinates (x0, y0, z0) of the discharge source are determined by solving them; Assume that there are N sensors, whose spatial positions are known, namely (x i ,y i , z i ), where i = 1, 2, 3, ... N, the three-dimensional coordinates of the discharge source are set to (x0, y0, z0), which is the target to be solved; the distance from the discharge source to the i-th sensor is: According to the propagation speed c of electromagnetic waves, the signal propagation time is: The actual measured time difference Δt i =t i -t1; Geometric model based on time difference: Select the first (x1, y1, z1) sensor as the reference point, and use the time difference between it and other sensors to build the geometric solution equation; for each sensor i, the following equation is obtained: The core of this set of equations is the distance difference between the two sensors and the discharge source, which is proportional to the time difference; The time difference Δt across all sensors i Construct N-1 equations, and finally form a nonlinear equation system: The form of the equation group is nonlinear. After solving it by the least square method or nonlinear optimization, (x0, y0, z0) is determined to realize the three-dimensional spatial positioning of the local discharge source.

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