A partial discharge positioning detection method for electrical equipment

Abstract

This invention relates to the field of electrical equipment condition monitoring technology and discloses a method for locating and detecting partial discharge in electrical equipment. The method includes: acquiring synchronized current pulse sequences and ultrasonic wave patterns using a pulse current sensor and an ultrasonic sensor; calculating the signal delay difference; establishing a multi-path acoustic wave propagation database based on the three-dimensional structure of the switchgear and the sensor coordinates; matching the ultrasonic wave pattern features with the database to determine the actual propagation path and equivalent distance; combining the delay difference, sensor coordinates, and equivalent distance, iteratively determining the optimal spatial coordinates of the discharge point using a particle swarm optimization algorithm; and mapping the coordinates to a topology map to generate a location report. This invention decouples the acoustic wave aliasing effect by pre-building a multi-path database, optimizes the delay correction and coordinate calculation process, and significantly improves positioning accuracy and efficiency.

Description

Technical Field

[0001] This invention relates to the field of electrical equipment condition monitoring technology, and in particular to a method for locating and detecting partial discharge in electrical equipment. Background Technology

[0002] In the field of power equipment condition monitoring, partial discharge localization is a key technology for diagnosing insulation defects. Due to the complex structure of metal-enclosed switchgear, the internal discharge acoustic waves undergo multiple reflections between the inner wall of the cavity and the insulating baffles, resulting in severe aliasing of ultrasonic signals. Traditional methods rely on manual experience to distinguish between direct and reflected waves, and the path identification process is significantly delayed, making it difficult to meet the timeliness requirements of fault early warning. Furthermore, the microsecond-level time delay difference between the pulse current and the ultrasonic signal, when uncorrected, can be amplified to meter-level spatial errors due to geometric relationships, requiring repeated iterative coordinate calculations, further limiting localization efficiency.

[0003] In existing technologies, acoustic wave path analysis often employs real-time simulation of reflection trajectories, with the computational load increasing exponentially with the complexity of the cavity. Distance errors caused by time delays require multiple iterative corrections using methods such as gradient descent, which is particularly time-consuming in large substation equipment inspection scenarios. Regional power grid service providers report that existing solutions take an average of over 20 minutes to locate within switchgear with dense reflection paths, and the results are easily influenced by subjective judgment. There is an urgent need for a location method that can automatically decouple acoustic wave multipath effects and optimize the time delay calculation architecture to meet the rapid diagnostic needs of high-density power equipment. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, embodiments of the present invention provide a method for locating and detecting partial discharge in electrical equipment to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides a method for locating and detecting partial discharge in electrical equipment, comprising:

[0006] S1. By connecting the grounding lead of the switchgear to the pulse current sensor and attaching the ultrasonic sensor to the insulating baffle of the switchgear, a synchronous current pulse sequence and ultrasonic wave are generated.

[0007] S2. Based on the current pulse sequence and the ultrasonic waveform, calculate the signal delay difference between the grounding lead and the sensor at the insulating baffle;

[0008] S3. Based on the three-dimensional structure of the metal cavity of the switch cabinet and the sensor layout coordinates, establish a multi-path database of acoustic wave propagation that includes direct paths and desired reflection paths;

[0009] S4. Match the first arriving wave feature identified in the ultrasonic wave pattern with the sound wave propagation multipath database to determine the actual sound wave propagation path type and the corresponding equivalent propagation distance;

[0010] S5. Combining the signal delay difference, the sensor deployment coordinates, and the equivalent propagation distance, the optimal spatial coordinates of the discharge point are determined iteratively through an optimization algorithm.

[0011] S6. Map the optimal spatial coordinates to the switch cabinet structure topology diagram to generate a partial discharge location report for the electrical equipment.

[0012] Optionally, the step of connecting the grounding lead of the switchgear via a pulse current sensor and attaching an ultrasonic sensor to the insulating baffle of the switchgear to generate a synchronized current pulse sequence and ultrasonic wave pattern includes:

[0013] The high-frequency current signal in the grounding lead is collected by a pulse current sensor and then filtered to generate a standardized current pulse sequence.

[0014] The ultrasonic sensor receives the acoustic wave signal inside the switch cabinet, and generates an ultrasonic wave after noise suppression processing.

[0015] A time synchronization device is used to clock-align the current pulse sequence with the ultrasonic wave pattern.

[0016] Optionally, calculating the signal delay difference between the grounding lead and the sensor at the insulating baffle based on the current pulse sequence and the ultrasonic waveform includes:

[0017] The peak time of the first pulse in the current pulse sequence is extracted as the reference time;

[0018] Identify the starting fluctuation point in the ultrasonic wave pattern that corresponds to the reference time;

[0019] Calculate the time difference between the reference time and the starting fluctuation point, and use it as the initial time delay difference.

[0020] Optionally, the step of establishing a multi-path acoustic wave propagation database containing direct paths and desired reflection paths based on the three-dimensional structure of the switch cabinet's metal cavity and the sensor layout coordinates includes:

[0021] Measure the inner wall dimensions, corner angles, and positions of insulating baffles of the switchgear metal cavity, and construct a three-dimensional structural model;

[0022] Mark the layout coordinates of the pulse current sensor and the ultrasonic sensor in the three-dimensional structural model to determine the straight-line distance between the sensors;

[0023] Simulate the direct path of sound waves from the discharge point to the ultrasonic sensor, and record the path length and propagation medium properties;

[0024] Simulate the desired reflection path of the sound wave after it is reflected by the metal cavity wall and the insulating baffle, and record the number of reflections, the coordinates of the reflection point, and the path length;

[0025] The parameters of the direct path and the desired reflection path are summarized to establish a multipath database for sound wave propagation.

[0026] Optionally, the simulated sound wave travels directly from the discharge point to the ultrasonic sensor, recording the path length and propagation medium properties, including:

[0027] A set of virtual discharge points is set in the three-dimensional structural model, and the set of virtual discharge points covers the potential discharge area of ​​the metal cavity of the switch cabinet.

[0028] For each virtual discharge point, a straight-line propagation trajectory from the virtual discharge point to the ultrasonic sensor is generated as a direct path, and the path length of the straight-line propagation trajectory and the sound speed characteristics of the propagation medium are recorded.

[0029] Optionally, the step of matching the first arrival wave feature identified in the ultrasonic wave pattern with the sound wave propagation multipath database to determine the actual sound wave propagation path type and the corresponding equivalent propagation distance includes:

[0030] The peak amplitude, rise slope, and waveform duration of the first arriving wave are extracted from the ultrasonic waveform as characteristic parameters of the arriving wave.

[0031] Call the theoretical waveform characteristic parameters corresponding to each path in the sound wave propagation multipath database;

[0032] Calculate the similarity between the characteristic parameters of the first arriving wave and the characteristic parameters of each theoretical waveform;

[0033] Based on the path corresponding to the theoretical waveform with the highest similarity, the actual sound wave propagation path type and equivalent propagation distance are determined.

[0034] Optionally, the step of combining the signal delay difference, the sensor deployment coordinates, and the equivalent propagation distance to iteratively determine the optimal spatial coordinates of the discharge point through an optimization algorithm includes:

[0035] Using the layout coordinates of the pulse current sensor and the ultrasonic sensor as boundary points, a cubic space including the line connecting the two and the surrounding area is delineated as the initial spatial coordinate range of the discharge point.

[0036] The distance constraint between the discharge point and the two sensors is determined based on the signal delay difference and the equivalent propagation distance.

[0037] Based on the aforementioned distance constraints, an objective function is constructed with the spatial coordinates of the discharge point as the variable. The output value of the objective function is the sum of the deviations from the distance constraints.

[0038] The objective function is calculated iteratively using a particle swarm optimization algorithm, and the candidate coordinates of the discharge point are updated in each iteration;

[0039] When the calculation error of the candidate coordinates is less than a preset threshold, the coordinates are output as the optimal spatial coordinates.

[0040] Optionally, the step of iteratively calculating the objective function using a particle swarm optimization algorithm, updating the candidate coordinates of the discharge point in each iteration, includes:

[0041] Initialize the particle positions of the particle swarm, with each particle corresponding to a candidate coordinate of the discharge point, and the particle positions are distributed within the range of the initial spatial coordinates;

[0042] Using the output value of the objective function as the fitness, the particle velocity and position are updated through a particle swarm optimization algorithm to iteratively optimize the candidate coordinates;

[0043] Calculate the objective function output value corresponding to the candidate coordinates after each iteration, and use this output value as the calculation error.

[0044] Optionally, the signal delay difference is used to correct the equivalent propagation distance, specifically including:

[0045] Calculate the time correction value for sound wave propagation based on the signal delay difference;

[0046] Based on the sound velocity of the air medium inside the switch cabinet, the time correction value is multiplied by the sound velocity to obtain the distance correction value;

[0047] The corrected actual propagation distance is obtained by subtracting the distance correction value from the equivalent propagation distance, wherein the corrected actual propagation distance is used as the input parameter for the optimization algorithm to solve iteratively.

[0048] Optionally, mapping the optimal spatial coordinates to the switchgear structural topology diagram and generating a partial discharge location report for the electrical equipment includes:

[0049] The optimal spatial coordinates are converted into two-dimensional coordinates in the switch cabinet structure topology diagram;

[0050] The internal components of the switchgear are marked with coordinates, and the internal components of the switchgear include busbars, insulators and circuit breakers;

[0051] The frequency and intensity of discharge points within a preset time period are statistically analyzed.

[0052] A location report is generated by combining the component attributes of the internal components of the switch cabinet, including the location, discharge intensity, and potential fault type.

[0053] Compared with the prior art, the present invention has the following beneficial effects:

[0054] This invention significantly improves the accuracy and efficiency of partial discharge localization by establishing a multi-path acoustic wave propagation database and optimizing the time delay correction architecture.

[0055] First, based on the three-dimensional structure of the switch cabinet, a database of acoustic wave propagation for direct and reflected paths is pre-constructed. Combined with ultrasonic shape feature matching technology, the actual propagation path type and equivalent propagation distance are automatically identified, effectively decoupling the signal aliasing problem caused by multi-path reflection, avoiding reliance on manual experience, and shortening the path analysis time.

[0056] Secondly, by dynamically correcting the equivalent propagation distance through signal delay difference, and combining sensor deployment coordinates with particle swarm optimization algorithm, a distance constraint objective function is constructed and the optimal spatial coordinates of the discharge point are iteratively obtained. This optimization architecture transforms the delay error into a spatial constraint condition, reduces repeated iterative calculations, significantly reduces positioning time, and improves the robustness of coordinate solution.

[0057] Finally, the discharge point is mapped to the structural topology map and associated with component attributes to generate a location report, providing an accurate basis for rapid diagnosis of insulation defects. Attached Figure Description

[0058] Figure 1 This is a flowchart illustrating a partial discharge location and detection method for electrical equipment according to an embodiment of the present invention.

[0059] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0060] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0061] This application provides a method for locating and detecting partial discharge in electrical equipment. The executing entity of this method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the method for locating and detecting partial discharge in electrical equipment can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks, and big data and artificial intelligence platforms.

[0062] Reference Figure 1 The diagram shown is a flowchart illustrating a partial discharge location and detection method for electrical equipment according to an embodiment of the present invention. In this embodiment, the partial discharge location and detection method for electrical equipment includes:

[0063] S1. By connecting the grounding lead of the switchgear to the pulse current sensor and attaching the ultrasonic sensor to the insulating baffle of the switchgear, a synchronous current pulse sequence and ultrasonic wave are generated.

[0064] In this embodiment of the invention, the step of connecting the grounding lead of the switchgear via a pulse current sensor and attaching an ultrasonic sensor to the insulating baffle of the switchgear to generate a synchronized current pulse sequence and ultrasonic wave pattern includes:

[0065] The high-frequency current signal in the grounding lead is collected by a pulse current sensor and then filtered to generate a standardized current pulse sequence.

[0066] The ultrasonic sensor receives the acoustic wave signal inside the switch cabinet, and generates an ultrasonic wave after noise suppression processing.

[0067] A time synchronization device is used to clock-align the current pulse sequence with the ultrasonic wave pattern.

[0068] In detail, a pulse current sensor is a device capable of detecting changes in current and converting them into a measurable signal. In practical applications, to obtain current information in the grounding down conductor, a pulse current sensor needs to be connected to the grounding down conductor of the switchgear. This operation is similar to connecting a monitoring node in a circuit; through the sensor's internal induction coil or other sensing elements, the current flowing through the grounding down conductor can be sensed.

[0069] For example, in common power facility layouts, the grounding down conductor is an important channel connecting the switchgear to the earth. When an electrical fault or other abnormal situation occurs inside the switchgear, an abnormal current will flow to the earth through the grounding down conductor. At this time, the pulse current sensor attached to the grounding down conductor can capture these current changes.

[0070] In detail, an ultrasonic sensor is a device used to detect sound wave signals. In this invention, it is attached to the insulating baffle of the switchgear. The insulating baffle is a component in the switchgear used to isolate electrical components and ensure electrical insulation performance. Attaching the ultrasonic sensor to it allows for the effective reception of sound wave signals generated inside the switchgear due to phenomena such as electrical discharge. For example, when partial discharge occurs inside the switchgear, ultrasonic waves are generated. The ultrasonic sensor attached to the insulating baffle can receive these ultrasonic signals and convert them into electrical signals for subsequent processing.

[0071] Specifically, the process of acquiring high-frequency current signals from the grounding lead using a pulse current sensor, and generating a standardized current pulse sequence after filtering, includes:

[0072] When a pulse current sensor is working, its internal induction mechanism senses the current in the grounding down conductor. In actual power system operation, in addition to potentially fault-related high-frequency current signals, the grounding down conductor also contains various low-frequency interference currents and environmental noise. To obtain accurate fault-related high-frequency current signals, the acquired raw current signal needs to be filtered. This filtering is typically achieved using a filter, which, based on its designed frequency characteristics, allows signals within a specific frequency range to pass through while blocking signals of other frequencies.

[0073] For example, a high-pass filter can be used, with its cutoff frequency set to filter out low-frequency interference signals, allowing only high-frequency current signals to pass through. After such filtering, a relatively pure high-frequency current signal is obtained.

[0074] Next, the filtered high-frequency current signal undergoes further processing to generate a standardized current pulse sequence. This process may involve operations such as amplitude adjustment and pulse shaping.

[0075] For example, a comparator circuit compares the filtered signal with a specific threshold. When the signal amplitude exceeds the threshold, a pulse signal with a standard amplitude is output. Through this series of processes, a standardized current pulse sequence with specific amplitude, width, and interval is ultimately formed. This standardized current pulse sequence facilitates subsequent analysis and processing, providing more accurate data for judging the operating status of the switchgear.

[0076] In detail, the process of receiving acoustic signals from inside the switchgear using an ultrasonic sensor and generating ultrasonic waves after noise suppression processing includes: after the ultrasonic sensor is attached to the insulating baffle of the switchgear, it receives various acoustic signals from inside the switchgear. However, in actual working environments, in addition to acoustic signals related to electrical faults inside the switchgear, there are also a large amount of environmental noise and interference acoustic signals generated by other equipment. In order to obtain acoustic signals that accurately reflect the electrical condition inside the switchgear, it is necessary to perform noise suppression processing on the raw acoustic signals received by the ultrasonic sensor.

[0077] Noise suppression can be achieved using various techniques, such as adaptive filtering algorithms based on digital signal processing. These algorithms automatically adjust filter parameters based on the characteristics of the received signal to suppress noise to the greatest extent possible. In practical applications, a sample of data containing noise but not the internal fault acoustic signal of the switchgear is first acquired. The initial parameters of the adaptive filter are determined by analyzing the statistical characteristics of this sample data. Then, when the ultrasonic sensor receives a mixed signal containing both fault acoustic signals and noise, the adaptive filter continuously adjusts its parameters based on the real-time received signal to suppress the noise. After noise suppression, a relatively pure acoustic signal related to the electrical phenomena inside the switchgear is obtained. This signal is further processed to generate ultrasonic waveforms. Generating ultrasonic waveforms may involve converting the signal into visualized waveform data, such as converting the analog acoustic signal into a digital signal using an analog-to-digital converter, and then using a graphics algorithm to generate the corresponding waveform on a display screen or data storage device. This allows for intuitive observation and analysis of the acoustic signal characteristics, which can provide important clues for determining whether a fault exists inside the switchgear and the type of fault.

[0078] Specifically, the step of using a time synchronization device to clock-align the current pulse sequence with the ultrasonic wave includes:

[0079] A time synchronization device is a device that provides a precise time reference and enables time synchronization between different devices or signals. In this invention, since the current pulse sequence and ultrasonic waveform are generated by different sensors, their temporal correspondence is crucial for accurately analyzing the operating status of the switchgear.

[0080] For example, when an electrical fault occurs inside a switchgear cabinet, the resulting current changes and acoustic signals are sequential and closely related in time. If the current pulse sequence and the ultrasonic wave pattern are out of sync, errors will occur when analyzing the correlation between the two, leading to inaccurate fault diagnosis.

[0081] Therefore, a time synchronization device is used to align the current pulse sequence with the ultrasonic wave. Time synchronization devices can achieve synchronization in various ways, with GPS-based synchronization being a common method. The GPS system provides high-precision time signals; after receiving the GPS signal, the time synchronization device calibrates its internal clock against the GPS time.

[0082] Then, the time synchronization device sends a synchronization clock signal to the pulse current sensor and the ultrasonic sensor. After receiving the synchronization clock signal, the pulse current sensor and the ultrasonic sensor use it as a reference to record the timestamp of the data they have collected.

[0083] In this way, when generating current pulse sequences and ultrasonic waveforms, the timing information they carry is based on the same time reference, thus achieving time alignment between the two. Clock alignment ensures that subsequent joint analysis of the current pulse sequences and ultrasonic waveforms can accurately determine the electrical phenomena inside the switchgear based on the time relationship, improving the accuracy and reliability of switchgear operation status monitoring and fault diagnosis.

[0084] S2. Based on the current pulse sequence and the ultrasonic waveform, calculate the signal delay difference between the grounding lead and the sensor at the insulating baffle.

[0085] In this embodiment of the invention, calculating the signal delay difference between the grounding lead and the sensor at the insulating baffle based on the current pulse sequence and the ultrasonic waveform includes:

[0086] The peak time of the first pulse in the current pulse sequence is extracted as the reference time;

[0087] Identify the starting fluctuation point in the ultrasonic wave pattern that corresponds to the reference time;

[0088] Calculate the time difference between the reference time and the starting fluctuation point, and use it as the initial time delay difference.

[0089] Specifically, the calculation of the signal delay difference between the grounding lead and the sensor at the insulating baffle based on the current pulse sequence and the ultrasonic waveform includes:

[0090] Signal delay difference refers to the time difference between two different signals arriving at the monitoring point during propagation. In this invention, the current pulse sequence is generated by a pulse current sensor, and the ultrasonic wave is generated by an ultrasonic sensor. Due to the different deployment locations of the two sensors and the differences in the signal generation and propagation paths, the arrival times of the two signals at their respective sensors will differ. Calculating this delay difference can provide a temporal reference for subsequently determining the location of the discharge point.

[0091] For example, when a partial discharge occurs inside the switch cabinet, both a current signal and an acoustic signal are generated simultaneously. The current signal propagates through the grounding lead, while the acoustic signal propagates through the air. The two signals arrive at the sensor at different times. By calculating the time delay difference, the location of the discharge point can be inferred by combining information such as the signal propagation speed.

[0092] Specifically, extracting the peak time of the first pulse in the current pulse sequence as a reference time includes: the current pulse sequence is a sequence of pulse signals, each pulse having its own amplitude variation. The peak time of the first pulse refers to the time point when the first pulse in the current pulse sequence reaches its maximum amplitude. This time is extracted as the reference time because when partial discharge occurs, the current signal usually first forms a detectable pulse, and the peak time of the first pulse has a clear marker, which can serve as the starting point for time reference.

[0093] During implementation, waveform analysis of the current pulse sequence is required. Digital signal processing techniques can be used to scan the generated standardized current pulse sequence. For example, a data acquisition frequency can be set, assuming 1000 data points are acquired per second, and the curve showing the amplitude of the current pulse sequence changing over time can be displayed. By traversing the data points, the time coordinate corresponding to the maximum amplitude of the first pulse in the sequence can be found; this time coordinate is the peak time of the first pulse. For instance, in the acquired sequence, the 100th data point corresponds to the maximum amplitude of the first pulse. If each data point is spaced 1 millisecond apart, the peak time of the first pulse is 100 milliseconds, which can be determined as the reference time.

[0094] Specifically, identifying the starting fluctuation point in the ultrasonic wave pattern corresponding to the reference time includes:

[0095] The initial fluctuation point refers to the point in the ultrasonic waveform where, corresponding to the reference time, significant fluctuations begin to appear. Because the acoustic signal generated by partial discharge takes time to propagate, the moment it begins to fluctuate in the ultrasonic waveform will be later than the reference time. Identifying this moment is to determine the time it takes for the acoustic signal to reach the ultrasonic sensor.

[0096] In implementation, a time correlation analysis between the ultrasonic waveform and the reference time is required. Based on the clock alignment already implemented by the time synchronization device, the time axis of the ultrasonic waveform is aligned with the time axis of the current pulse sequence. The ultrasonic waveform is monitored in real time. Once the reference time is determined, the corresponding position on the time axis of the ultrasonic waveform is located, and the waveform changes after that position are observed. When the waveform begins to show significant amplitude fluctuations from a relatively stable state, the starting point of this fluctuation is the initial fluctuation point. For example, if the reference time is 100 milliseconds, in the ultrasonic waveform, after 100 milliseconds, starting from 102 milliseconds, the amplitude of the waveform begins to fluctuate from its previous stable value; therefore, 102 milliseconds is the corresponding initial fluctuation point.

[0097] The technical effect of this step is to determine the arrival time of the sound wave signal. In conjunction with the reference time, it provides another key time point for calculating the time delay difference, thus solving the problem of not being able to accurately obtain the arrival time of the sound wave signal.

[0098] Specifically, calculating the time difference between the reference time and the initial fluctuation point as the initial time delay difference includes:

[0099] The time difference refers to the interval between two different points in time. In this invention, the time difference between the reference time and the initial fluctuation point is calculated, and the result is the initial time delay difference. This difference reflects the time difference between the arrival of the current signal and the sound wave signal at their respective sensors.

[0100] The process involves subtracting the time values ​​of the determined base time and the starting fluctuation point. For example, if the base time is 100 milliseconds and the starting fluctuation point is 102 milliseconds, then the time difference is 102 milliseconds minus 100 milliseconds, which equals 2 milliseconds. This 2 milliseconds is used as the initial time delay difference.

[0101] This step yielded the time difference between the propagation of the two signals, providing crucial data for subsequent distance calculations based on propagation speed, and solving the problem of being unable to infer the differences in propagation paths due to unknown time differences.

[0102] In summary, a complete time delay difference calculation process is formed, from determining the reference time to identifying the corresponding initial fluctuation point and then calculating the time difference. Through these steps, the signal time delay difference is accurately obtained, providing important time parameters for subsequent establishment of a sound wave propagation path database and determination of the discharge point coordinates. Overall, this solves the problem of large positioning errors caused by inaccurate time information in traditional partial discharge positioning. In particular, extracting the peak time of the first pulse and identifying the corresponding initial fluctuation point improves the accuracy of time delay difference calculation by using a clear time reference and corresponding fluctuation point identification.

[0103] S3. Based on the three-dimensional structure of the switch cabinet's metal cavity and the sensor layout coordinates, establish a multi-path database for acoustic wave propagation that includes direct paths and desired reflection paths.

[0104] In this embodiment of the invention, establishing a multi-path acoustic wave propagation database containing direct paths and desired reflection paths based on the three-dimensional structure of the switch cabinet's metal cavity and the sensor layout coordinates includes:

[0105] Measure the inner wall dimensions, corner angles, and positions of insulating baffles of the switchgear metal cavity, and construct a three-dimensional structural model;

[0106] Mark the layout coordinates of the pulse current sensor and the ultrasonic sensor in the three-dimensional structural model to determine the straight-line distance between the sensors;

[0107] Simulate the direct path of sound waves from the discharge point to the ultrasonic sensor, and record the path length and propagation medium properties;

[0108] Simulate the desired reflection path of the sound wave after it is reflected by the metal cavity wall and the insulating baffle, and record the number of reflections, the coordinates of the reflection point, and the path length;

[0109] The parameters of the direct path and the desired reflection path are summarized to establish a multipath database for sound wave propagation.

[0110] In detail, the simulated sound wave travels directly from the discharge point to the ultrasonic sensor, recording the path length and propagation medium properties, including:

[0111] A set of virtual discharge points is set in the three-dimensional structural model, and the set of virtual discharge points covers the potential discharge area of ​​the metal cavity of the switch cabinet.

[0112] For each virtual discharge point, a straight-line propagation trajectory from the virtual discharge point to the ultrasonic sensor is generated as a direct path, and the path length of the straight-line propagation trajectory and the sound speed characteristics of the propagation medium are recorded.

[0113] In detail, the establishment of a multi-path acoustic wave propagation database, including direct paths and desired reflection paths, based on the three-dimensional structure of the switch cabinet's metal cavity and the sensor deployment coordinates, includes:

[0114] The acoustic wave propagation multipath database is a collection storing information related to the possible propagation paths of acoustic waves within the metal cavity of a switchgear. The direct path is the path from the discharge point directly to the ultrasonic sensor. The desired reflection path is the path from the discharge point, reflected by the metal cavity wall or insulating baffle, to the ultrasonic sensor. This database was established to subsequently match the corresponding propagation paths based on the actual detected acoustic wave characteristics, thus providing a path basis for locating the discharge point.

[0115] In detail, the measurement of the inner wall dimensions, corner angles, and insulating baffle positions of the switchgear metal cavity is used to construct a three-dimensional structural model, including:

[0116] The metal cavity of a switchgear is a closed or semi-closed space made of metal inside the switchgear, serving as the installation and operation site for electrical components. Internal wall dimensions refer to the length, width, height, and other dimensions of each inner wall of the metal cavity. Corner angles refer to the angles between two intersecting inner walls at each corner of the metal cavity. Insulating baffle positions refer to the specific spatial locations of the insulating baffles within the metal cavity. A three-dimensional structural model is a digital model that visually displays the three-dimensional structure of the switchgear's metal cavity.

[0117] In practice, a laser rangefinder can be used to measure the inner dimensions of the switchgear's metal cavity. For example, the length, width, and height of the cavity can be measured, assuming a length of 5 meters, a width of 3 meters, and a height of 2 meters. For corner angles, an angle measuring instrument can be used, e.g., measuring a corner angle of 90 degrees. For the location of the insulating baffle, reference points are set on the inner wall of the cavity, and the distance from the baffle edge to each reference point is measured to determine its position. For example, using the lower left corner of the cavity bottom as the reference point, the horizontal distance from a certain edge of the baffle to the reference point is measured to be 1 meter, and the vertical distance is 0.5 meters. These measured data are then input into 3D modeling software, such as AutoCAD or SolidWorks. The software will automatically construct a 3D structural model of the switchgear's metal cavity based on the input dimensions, angles, and position information. This model accurately reflects the cavity's three-dimensional shape and the relative positions of each component.

[0118] Specifically, marking the placement coordinates of the pulse current sensor and the ultrasonic sensor in the three-dimensional structural model and determining the straight-line distance between the sensors includes:

[0119] The deployment coordinates refer to the spatial coordinates of the sensor in the three-dimensional structural model, composed of values ​​in the X, Y, and Z dimensions, used to accurately represent the sensor's position. The straight-line distance between sensors refers to the length of the pulse current sensor and the ultrasonic sensor connected by a straight line in three-dimensional space.

[0120] The process involves finding the corresponding points in the three-dimensional structural model based on the actual positions of the pulse current sensor attached to the grounding lead and the ultrasonic sensor attached to the insulating baffle. For example, in the three-dimensional model, the coordinates of the pulse current sensor are determined to be (0,0,0), and the coordinates of the ultrasonic sensor are (5,3,2). Then, using the formula for calculating the distance between two points in three-dimensional space, i.e., when the coordinates of the two points are (X1,Y1,Z1) and (X2,Y2,Z2), the above coordinates are substituted into the Euclidean distance calculation formula to calculate the straight-line distance between the two sensors, which is found to be 6.16 meters.

[0121] In summary, the three-dimensional structural model constructed in the previous step provides a platform for marking the coordinates of the sensor deployment in this step. Without the three-dimensional model, it is impossible to accurately mark the sensor coordinates and calculate the straight-line distance in virtual space.

[0122] In detail, the simulated sound wave travels directly from the discharge point to the ultrasonic sensor, recording the path length and propagation medium properties, including:

[0123] The discharge point is the location where a partial discharge occurs inside the switchgear. The direct path is the path that the sound wave takes from the discharge point and propagates directly to the ultrasonic sensor without any reflection. The path length refers to the spatial length of this direct path. The propagation medium properties refer to the characteristics of the medium through which the sound wave travels during propagation. In this scenario, the propagation medium is mainly air, and its properties include air temperature, humidity, and the speed of sound wave propagation in that medium.

[0124] In implementation, based on the constructed 3D structural model, it is assumed that a discharge point exists within the model. For example, the coordinates of a discharge point are set to (2,1,1). Then, a straight line is drawn in the model from this discharge point to the ultrasonic sensor coordinates (5,3,2). This straight line represents the direct path of sound wave propagation. The length of this straight line is measured using the distance measurement tool in the model, assuming the path length is 4 meters. Regarding the propagation medium properties, since the sound wave propagates in the air inside the switchgear, a temperature and humidity sensor can be placed inside the switchgear to measure the current air temperature as 25 degrees Celsius and the humidity as 50%. According to acoustic principles, under these temperature and humidity conditions, the speed of sound in the air is approximately 346 meters per second. This medium property information is recorded.

[0125] Specifically, the step of setting a set of virtual discharge points in the three-dimensional structural model, the set of virtual discharge points covering the potential discharge area of ​​the switchgear metal cavity, includes:

[0126] A set of virtual discharge points refers to a collection of multiple virtual points that may potentially discharge, defined in a three-dimensional structural model. A potential discharge area refers to a region within the metal cavity of a switchgear that is prone to partial discharge, typically where electrical components are concentrated or insulation is easily damaged.

[0127] In implementation, the potential discharge area is first determined based on the switchgear structure and the distribution of electrical components. For example, in the switchgear, the connection points between the busbar and the insulator, and the contact points of the circuit breaker are all potential discharge areas. Then, multiple virtual discharge points are uniformly or as needed set within these areas in the three-dimensional structural model. Assuming 100 virtual discharge points are set within the potential discharge area, with the coordinates of each point as (x1, y1, z1), (x2, y2, z2)...(x100, y100, z100), these points together constitute the set of virtual discharge points, which can fully cover the potential discharge area.

[0128] Specifically, for each virtual discharge point, generating a straight-line propagation trajectory from the virtual discharge point to the ultrasonic sensor as a direct path, and recording the path length of the straight-line propagation trajectory and the sound speed characteristics of the propagation medium, includes:

[0129] A straight-line propagation trajectory refers to the trajectory formed by a straight line from the virtual discharge point to the ultrasonic sensor. Sound velocity characteristics refer to the propagation speed of sound waves in a propagation medium, that is, the magnitude of the speed at which sound waves propagate in that medium.

[0130] In implementation, for each virtual discharge point in the set of virtual discharge points, for example, one virtual discharge point with coordinates (1, 0.5, 0.5), a straight line from that point to the ultrasonic sensor coordinates (5, 3, 2) is generated in the 3D structural model using software. This straight line is the direct path of the virtual discharge point. The length of this straight line is measured using the model's measurement function; assuming a path length of 3 meters, the path length is assumed to be 3 meters. Regarding the sound velocity characteristics of the propagation medium, since the propagation medium is air, combined with previously measured air temperature and humidity, the sound velocity is determined to be 346 meters per second. This sound velocity characteristic and the path length are recorded together.

[0131] In detail, the simulation of the desired reflection path of the sound wave after reflection by the metal cavity wall and the insulating baffle, and the recording of the number of reflections, the coordinates of the reflection point, and the path length, includes:

[0132] The desired reflection path refers to the simulated path of a sound wave after reflection from the metal cavity wall or insulating baffle, based on the laws of sound wave propagation. The number of reflections refers to the number of times the sound wave is reflected by the wall or baffle during propagation. The reflection point coordinates refer to the spatial coordinates of the point on the wall or baffle where the sound wave is reflected.

[0133] In implementation, a three-dimensional structural model and the law of sound wave reflection (i.e., the incident angle equals the reflection angle) are used to simulate the reflection path. For example, for a virtual discharge point (2,1,1), the simulated sound wave first propagates to a wall of the metal cavity, assuming this wall is the right side wall (X=5 meters). The reflection point of the sound wave reaching this wall is calculated. According to the law of reflection, the coordinates of the reflection point are calculated and assumed to be (5,2,1.5). Then, the sound wave propagates from this reflection point to the ultrasonic sensor (5,3,2). This path is the expected reflection path for one reflection. The number of reflections is recorded as 1, the coordinates of the reflection point (5,2,1.5), and the total length of the path is measured, assumed to be 5 meters. As another example, the simulated sound wave first reflects from the left side wall, then from the insulating baffle, and finally reaches the sensor. The number of reflections is recorded as 2, along with the corresponding reflection point coordinates and path length.

[0134] Specifically, the step of summarizing the parameters of the direct path and the desired reflection path to establish a multipath database for sound wave propagation includes:

[0135] Parameter aggregation refers to the process of collecting, organizing, and centrally storing various parameters of the direct path and the desired reflection path. The acoustic wave propagation multipath database is a structured collection of data that stores these aggregated parameters.

[0136] In implementation, the database structure is designed, setting fields such as path type (direct or reflective), path length, propagation medium properties, number of reflections, and reflection point coordinates. Then, the parameters of the direct path and desired reflection path recorded in the previous steps are entered according to the database structure requirements. For example, for a direct path, information such as path type "direct," path length "4 meters," and propagation medium sound speed "346 m / s" is entered; for a reflective path, information such as path type "reflective," number of reflections "1," reflection point coordinates "(5,2,1.5)," and path length "5 meters" is entered. All this information is integrated into the database to form a complete multipath database for sound wave propagation.

[0137] In summary, from constructing the 3D model to establishing a multi-path database, comprehensive foundational data is provided for identifying sound wave propagation paths. In particular, simulating multiple paths and summarizing parameters to establish a database overcomes the limitations of traditional methods that only consider direct paths, comprehensively considering possible reflection paths. This makes the judgment of sound wave propagation paths more accurate, thereby improving the precision of partial discharge localization.

[0138] S4. Match the first arriving wave feature identified in the ultrasonic wave pattern with the sound wave propagation multipath database to determine the actual sound wave propagation path type and the corresponding equivalent propagation distance.

[0139] In this embodiment of the invention, the step of matching the first arrival wave feature identified in the ultrasonic wave pattern with the sound wave propagation multipath database to determine the actual sound wave propagation path type and the corresponding equivalent propagation distance includes:

[0140] The peak amplitude, rise slope, and waveform duration of the first arriving wave are extracted from the ultrasonic waveform as characteristic parameters of the arriving wave.

[0141] Call the theoretical waveform characteristic parameters corresponding to each path in the sound wave propagation multipath database;

[0142] Calculate the similarity between the characteristic parameters of the first arriving wave and the characteristic parameters of each theoretical waveform;

[0143] Based on the path corresponding to the theoretical waveform with the highest similarity, the actual sound wave propagation path type and equivalent propagation distance are determined.

[0144] Specifically, the step of matching the first arriving wave feature identified in the ultrasonic wave pattern with the sound wave propagation multipath database to determine the actual sound wave propagation path type and the corresponding equivalent propagation distance includes:

[0145] The first arriving wave characteristic refers to the features of the first sound wave to arrive at the ultrasonic sensor in an ultrasonic waveform. These features reflect the propagation path information of the sound wave. The actual sound wave propagation path type refers to whether the path taken by the sound wave from the discharge point to the ultrasonic sensor is a direct path or a reflection path. The equivalent propagation distance is the length of the actual sound wave propagation path, which is an important parameter for subsequent calculation of the discharge point location. By matching, the actually detected sound wave characteristics can be associated with the preset path characteristics in the database, thereby determining the actual propagation path and the corresponding distance.

[0146] Specifically, the extraction of the peak amplitude, rise slope, and waveform duration of the first arriving wave from the ultrasonic waveform as characteristic parameters of the arriving wave includes:

[0147] Peak amplitude refers to the largest amplitude value in the waveform of the first arriving wave, reflecting the energy of the sound wave upon reaching the sensor. Rise slope refers to the rate at which the amplitude of the first arriving wave changes over time as it rises from its initial fluctuation point to its peak amplitude. Waveform duration refers to the time elapsed from the initial fluctuation point of the first arriving wave until the waveform returns to a stationary state. Arrival wave characteristic parameters are specific values ​​used to describe the characteristics of the first arriving wave.

[0148] In implementation, signal processing software is used to analyze the ultrasonic waveform. For example, in the acquired ultrasonic waveform, the waveform of the first arriving wave exhibits obvious fluctuations. For the peak amplitude, the software scans the waveform data to find the maximum amplitude, assuming a peak amplitude of 5 millivolts. For the rise slope, the waveform segment from the initial fluctuation point to the peak amplitude point is selected, and the ratio of the amplitude change to the time change is calculated. Assuming the amplitude rises from 0 to 5 millivolts in 2 milliseconds, the rise slope is 2.5 millivolts / millisecond. For the waveform duration, the initial fluctuation point and the end point of the first arriving wave are determined, and the time difference between the two points is calculated. Assuming the start is 102 milliseconds and the end is 110 milliseconds, the waveform duration is 8 milliseconds. These three parameters are extracted as characteristic parameters of the arriving wave.

[0149] Specifically, the step of calling the theoretical waveform characteristic parameters corresponding to each path in the sound wave propagation multipath database includes:

[0150] Theoretical waveform characteristic parameters refer to the characteristic parameters of the acoustic waveform corresponding to a path, obtained through theoretical calculation or simulation based on the parameters of each path in the acoustic propagation multipath database. These parameters include the theoretical peak amplitude, rise slope, and waveform duration.

[0151] In implementation, a database query command is used to retrieve the theoretical waveform characteristic parameters of each path from an established multipath acoustic propagation database. For example, the database stores the theoretical parameters of one direct path and two reflection paths. The theoretical peak amplitude of the direct path is 6 mV, the rise slope is 3 mV / ms, and the waveform duration is 7 ms; the theoretical peak amplitude of the first reflection path is 4 mV, the rise slope is 2 mV / ms, and the waveform duration is 9 ms; the theoretical peak amplitude of the second reflection path is 3 mV, the rise slope is 1.5 mV / ms, and the waveform duration is 10 ms. These parameters are retrieved one by one for subsequent similarity calculations.

[0152] In detail, the calculation of the similarity between the characteristic parameters of the first arriving wave and the characteristic parameters of each theoretical waveform includes:

[0153] Similarity refers to the degree of similarity between the characteristic parameters of the first arriving wave and the characteristic parameters of each theoretical waveform. The higher the similarity, the closer the actual sound wave is to the sound wave characteristics corresponding to the theoretical path.

[0154] In implementation, a feature parameter comparison method is used to calculate similarity. The differences between the actual arriving wave feature parameters and the corresponding parameters in the theoretical waveform feature parameters for each theoretical path are calculated separately, and then these differences are combined to obtain the similarity score. For example, the differences in peak amplitude, rising edge slope, and waveform duration are used as the basis for calculation, with each parameter having the same weight. The actual parameters are a peak amplitude of 5 mV, a rising edge slope of 2.5 mV / ms, and a waveform duration of 8 ms. For the theoretical parameters of the direct path, the difference in peak amplitude is 1 mV, the difference in rising edge slope is 0.5 mV / ms, and the difference in waveform duration is 1 ms, for a total difference of 2.5. For the theoretical parameters of the first reflection path, the difference in peak amplitude is 1 mV, the difference in rising edge slope is 0.5 mV / ms, and the difference in waveform duration is 1 ms, for a total difference of 2.5. For the theoretical parameters of the second reflection path, the difference in peak amplitude is 2 mV, the difference in rising edge slope is 1 mV / ms, and the difference in waveform duration is 2 ms, for a total difference of 5. The smaller the total difference, the higher the similarity. Therefore, the actual parameters are more similar to the theoretical parameters of the first two paths than to the third path.

[0155] In detail, determining the actual sound wave propagation path type and equivalent propagation distance based on the path corresponding to the theoretical waveform with the highest similarity includes:

[0156] The actual sound wave propagation path type refers to whether the actual sound wave's propagation path, determined based on the matching results, is a direct path or a reflection path. The equivalent propagation distance refers to the length of the path corresponding to the theoretical waveform with the highest similarity.

[0157] In implementation, the calculated similarity scores of each path are compared to identify the path corresponding to the theoretical waveform with the highest similarity. For example, after comparison, it is found that the total difference between the actual arriving wave characteristic parameters and the theoretical parameters of the direct path is 2.5, and the total difference between the actual arriving wave characteristic parameters and the theoretical parameters of the first reflection path is also 2.5. At this point, the matching degree of each parameter can be further analyzed. If the differences in peak amplitude and rising slope are smaller, then one of them can be determined as the path with the highest similarity. Assuming that the direct path is ultimately determined to be the path with the highest similarity, then the actual sound wave propagation path type is the direct path. The path length of this direct path recorded in the database is 4 meters, therefore the equivalent propagation distance is 4 meters.

[0158] In summary, this step achieves accurate identification of the actual sound wave propagation path through a series of operations including extracting feature parameters, calling theoretical parameters, calculating similarity, and determining the actual path. Specifically, matching the actual feature parameters with theoretical parameters in the database, and using a multi-parameter comprehensive comparison method, improves the accuracy of path identification and provides crucial path information for subsequent precise location of the discharge point, thus forming a complete path identification process.

[0159] S5. Combining the signal delay difference, the sensor deployment coordinates, and the equivalent propagation distance, the optimal spatial coordinates of the discharge point are obtained through iterative optimization algorithm.

[0160] In this embodiment of the invention, the step of combining the signal delay difference, the sensor deployment coordinates, and the equivalent propagation distance to iteratively determine the optimal spatial coordinates of the discharge point through an optimization algorithm includes:

[0161] Using the layout coordinates of the pulse current sensor and the ultrasonic sensor as boundary points, a cubic space including the line connecting the two and the surrounding area is delineated as the initial spatial coordinate range of the discharge point.

[0162] The distance constraint between the discharge point and the two sensors is determined based on the signal delay difference and the equivalent propagation distance.

[0163] Based on the aforementioned distance constraints, an objective function is constructed with the spatial coordinates of the discharge point as the variable. The output value of the objective function is the sum of the deviations from the distance constraints.

[0164] The objective function is calculated iteratively using a particle swarm optimization algorithm, and the candidate coordinates of the discharge point are updated in each iteration;

[0165] When the calculation error of the candidate coordinates is less than a preset threshold, the coordinates are output as the optimal spatial coordinates.

[0166] In detail, the step of iteratively calculating the objective function using the particle swarm optimization algorithm, updating the candidate coordinates of the discharge point in each iteration, includes:

[0167] Initialize the particle positions of the particle swarm, with each particle corresponding to a candidate coordinate of the discharge point, and the particle positions are distributed within the range of the initial spatial coordinates;

[0168] Using the output value of the objective function as the fitness, the particle velocity and position are updated through a particle swarm optimization algorithm to iteratively optimize the candidate coordinates;

[0169] Calculate the objective function output value corresponding to the candidate coordinates after each iteration, and use this output value as the calculation error.

[0170] Specifically, the signal delay difference is used to correct the equivalent propagation distance, and includes:

[0171] Calculate the time correction value for sound wave propagation based on the signal delay difference;

[0172] Based on the sound velocity of the air medium inside the switch cabinet, the time correction value is multiplied by the sound velocity to obtain the distance correction value;

[0173] The corrected actual propagation distance is obtained by subtracting the distance correction value from the equivalent propagation distance, wherein the corrected actual propagation distance is used as the input parameter for the optimization algorithm to solve iteratively.

[0174] In detail, the step of combining the signal delay difference, the sensor deployment coordinates, and the equivalent propagation distance to iteratively determine the optimal spatial coordinates of the discharge point through an optimization algorithm includes:

[0175] The optimal spatial coordinates refer to the three-dimensional coordinates that most accurately represent the position of the discharge point within the metal cavity of the switchgear. The signal delay difference is the time difference between the arrival of the current signal and the acoustic signal at the sensor. The sensor deployment coordinates are the specific locations of the pulse current sensor and the ultrasonic sensor in three-dimensional space. The equivalent propagation distance is the length of the actual acoustic wave propagation path. The optimization algorithm iteratively solves this problem by continuously adjusting the assumed coordinates of the discharge point using mathematical calculations, ultimately finding the coordinates that best reflect the actual situation.

[0176] Specifically, the initial spatial coordinate range of the discharge point, defined by using the deployment coordinates of the pulse current sensor and the ultrasonic sensor as boundary points and delineating a cubic space including the line connecting the two and the surrounding area, includes:

[0177] Boundary points refer to the coordinates of the pulse current sensor and the ultrasonic sensor in three-dimensional space; they serve as reference points for defining the initial spatial range. The cubic space refers to the three-dimensional space formed by the line connecting the two sensors and the surrounding area, with the coordinates of the two sensors as boundary points. The initial spatial coordinate range refers to the preliminary setting of the spatial range where the discharge point may exist; this range provides the search boundary for subsequent iterative calculations.

[0178] In implementation, the known coordinates of the pulse current sensor are (0,0,0) and the coordinates of the ultrasonic sensor are (5,3,2). Based on these two coordinates, a cubic space is defined in three-dimensional space. The side length of the cube can be set according to the actual size of the switch cabinet. For example, based on the connection between the two sensors, if it is extended by 1 meter in each direction, then the x-axis range of the cube is -1 to 6, the y-axis range is -1 to 4, and the z-axis range is -1 to 3. This cubic space includes the connection between the two sensors and the surrounding area. Using this as the initial spatial coordinate range of the discharge point means that the coordinates of the discharge point are likely within this range.

[0179] Specifically, determining the distance constraint condition between the discharge point and the two sensors based on the signal delay difference and the equivalent propagation distance includes:

[0180] Distance constraints refer to the conditions that must be met by the distance between the discharge point and the pulse current sensor and the ultrasonic sensor, derived from the signal delay difference and equivalent propagation distance. These conditions are based on the propagation laws of sound waves and current and are used to limit the possible location of the discharge point.

[0181] In implementation, we assume a signal delay difference of 2 milliseconds and an equivalent propagation distance of 4 meters. Since the propagation speed of current signals is extremely fast, we can assume the propagation time from the discharge point to the pulse current sensor is 0. Therefore, the distance from the discharge point to the pulse current sensor can be derived through other relationships. The distance from the discharge point to the ultrasonic sensor is the equivalent propagation distance of 4 meters. Furthermore, based on the signal delay difference, the time it takes for the sound wave to propagate 4 meters should be equal to the signal delay difference plus the propagation time of the current signal (approximately 0). Combining this with the speed of sound (346 m / s), we can verify the rationality of 4 meters and 2 milliseconds (346 m / s × 0.002 s ≈ 0.69 meters; however, due to reflections, the actual equivalent propagation distance needs to be adjusted accordingly; this is only an example logic). Therefore, the distance constraints are: the distance from the discharge point to the ultrasonic sensor is approximately 4 meters, and the distance to the pulse current sensor must satisfy the relationship with the sound wave propagation time.

[0182] Specifically, based on the distance constraints, a target function is constructed with the spatial coordinates of the discharge point as the variable. The output value of the target function is the sum of the deviations from the distance constraints, including:

[0183] The objective function is a mathematical function used to measure the degree to which the assumed coordinates of the discharge point conform to the distance constraints. The discharge point spatial coordinates are the variable, meaning the function's input is the three-dimensional coordinates (x, y, z) of the discharge point, and the calculation result changes with these coordinates. The total deviation of the distance constraints is the sum of the differences between the assumed discharge point coordinates and each distance constraint; the smaller the total deviation, the more closely the coordinate assumptions conform to reality.

[0184] In implementation, let the spatial coordinates of the discharge point be (x, y, z), the coordinates of the pulse current sensor be (0, 0, 0), and the coordinates of the ultrasonic sensor be (5, 3, 2). According to the distance formula, the distance from the discharge point to the ultrasonic sensor is... This distance should be equal to the equivalent propagation distance of 4 meters, with a deviation of [missing information]. .

[0185] Simultaneously, the distance constraint from the discharge point to the pulse current sensor is determined by considering factors such as signal delay difference. Assuming it represents a certain value, its deviation can be similarly expressed. The objective function is the sum of these deviations, i.e. , where L is the deviation of other distance constraints.

[0186] This step transforms the problem of finding the coordinates of the discharge point into the problem of optimizing a mathematical function, solving the problem of not being able to systematically solve the coordinates due to the lack of a mathematical model. Distance constraints are the basis for constructing the objective function, and the objective function is the mathematical expression of the distance constraints. Without distance constraints, it is impossible to construct the objective function.

[0187] In detail, the step of iteratively calculating the objective function using the particle swarm optimization algorithm, updating the candidate coordinates of the discharge point in each iteration, includes:

[0188] Particle Swarm Optimization (PSO) is a swarm intelligence-based optimization algorithm that simulates the foraging behavior of birds, allowing multiple candidate solutions (particles) to move continuously in the search space to find the optimal solution. Candidate coordinates refer to the hypothetical possible coordinates of the discharge point during iterative calculations; these coordinates are continuously updated with each iteration. Iterative calculation refers to repeatedly performing the calculation process, adjusting the candidate coordinates based on the previous result in each iteration, gradually approaching the optimal solution.

[0189] In implementation, a particle swarm is initialized within an initial spatial coordinate range. Assuming there are 50 particles, each representing candidate coordinates for a discharge point, these coordinates are randomly distributed within a cubic space. For example, a particle's initial candidate coordinates might be (2, 1, 1). Each candidate coordinate is substituted into the objective function to calculate the total deviation. According to the rules of the particle swarm optimization algorithm, each particle adjusts its movement direction and distance based on its historical best position and the global best position of the entire particle swarm. For example, if a particle's current candidate coordinates correspond to a total deviation of 3, its historical best deviation is 2, and the global best deviation is 1, then the particle will move towards the global best position, and its updated candidate coordinates might be (2.5, 1.2, 1.1). Each iteration updates the candidate coordinates of all particles, repeating this process.

[0190] Specifically, the initial particle swarm's particle positions, where each particle corresponds to a candidate coordinate of a discharge point, and the particle positions are distributed within the initial spatial coordinate range, include:

[0191] Particle position refers to the specific coordinate value of a particle within the initial spatial coordinate range. Each particle position corresponds to a hypothetical candidate coordinate for a discharge point. Initialization refers to assigning an initial position to each particle in the particle swarm before the iterative calculation begins.

[0192] In implementation, a random number generator is used to generate coordinates for each particle based on the x, y, and z axis ranges of the initial spatial coordinates. For example, if the initial x-axis range is -1 to 6, the y-axis range is -1 to 4, and the z-axis range is -1 to 3, for 50 particles, the x-coordinate of each particle is randomly generated between -1 and 6, the y-coordinate between -1 and 4, and the z-coordinate between -1 and 3, ensuring that all particle positions are distributed within the initial spatial coordinate range. For instance, if the initial position of one particle is (1, 0.5, 0.5), this position is a candidate coordinate for a discharge point.

[0193] This step provides the initial search starting point for the particle swarm optimization algorithm, solving the problem of being unable to start iterative calculations due to the lack of initial candidate coordinates. The previous step determined the initial spatial coordinate range, providing the spatial boundary for initializing particle positions in this step; particle positions can only be generated within this range.

[0194] Specifically, the step of using the output value of the objective function as fitness, updating the particle velocity and position through a particle swarm optimization algorithm, and iteratively optimizing the candidate coordinates includes:

[0195] Fitness is a metric used to evaluate the quality of a particle's position. In this invention, the output value of the objective function (the sum of deviations) is the fitness. The smaller the fitness, the closer the candidate coordinates corresponding to the particle's position are to the optimal solution. Particle velocity refers to the speed and direction of a particle's movement in three-dimensional space, which determines the magnitude and direction of the particle's position update. Iterative optimization refers to continuously updating the particle's velocity and position to gradually bring the candidate coordinates closer to the optimal solution.

[0196] In implementation, the fitness of each particle is the output value of the objective function corresponding to that particle. For example, if one particle has a fitness of 2.5 and another particle has a fitness of 1.8, then the particle with a fitness of 1.8 has a better position. According to the particle swarm optimization algorithm, the particle velocity update formula can be expressed as: New velocity = Inertia factor × Current velocity + Individual learning factor × Random number × (Individual optimal position - Current position) + Population learning factor × Random number × (Population optimal position - Current position).

[0197] Assuming the inertia factor is 0.5, the individual learning factor is 1, the group learning factor is 1, the current velocity of a certain particle is (0.1, 0.1, 0.1), the difference between the individual's optimal position and the current position is (0.5, 0.3, 0.2), the difference between the group's optimal position and the current position is (1, 0.8, 0.5), and the random number is 0.5, then the new velocity v = 0.5 × (0.1, 0.1, 0.1) + 1 × 0.5 × (0.5, 0.3, 0.2) + 1 × 0.5 × (1, 0.8, 0.5) = (0.05 + 0.25 + 0.5, 0.05 + 0.15 + 0.4, 0.05 + 0.1 + 0.25) = (0.8, 0.6, 0.4). The particle position is updated based on the new velocity. The new position = current position + new velocity. For example, if the current position is (2,1,1), then the new position is (2.8,1.6,1.4), which is the optimized candidate coordinate.

[0198] This step, through scientific speed and position update rules, guides particles to move towards the optimal solution, solving the problem of lack of basis for candidate coordinate updates and improving the efficiency of iterative optimization.

[0199] Specifically, the calculation of the objective function output value corresponding to the candidate coordinates after each iteration, and using this output value as the calculation error, includes:

[0200] The calculation error refers to the output value (total deviation) of the objective function corresponding to the candidate coordinates after each iteration. It reflects the degree of deviation between the current candidate coordinates and the actual discharge point coordinates.

[0201] In implementation, after updating the candidate coordinates of the particles in each iteration, the new candidate coordinates are substituted into the objective function for calculation. For example, if the candidate coordinates of a particle after iteration are (3, 2, 1.5), these coordinates are substituted into the objective function. The calculated output value is 1.2, which is the calculation error corresponding to the candidate coordinate.

[0202] This step provides a basis for determining whether the iteration has converged, solving the problem of not being able to determine when to stop the iteration because the quality of candidate coordinates cannot be measured.

[0203] Specifically, the step of outputting the candidate coordinates as the optimal spatial coordinates when the calculation error of the candidate coordinates is less than a preset threshold includes:

[0204] The preset threshold refers to a pre-defined error limit. When the calculation error is less than this limit, it indicates that the candidate coordinates are sufficiently close to the actual discharge point coordinates. The optimal spatial coordinates refer to the candidate coordinates whose calculation error is less than the preset threshold; it is the final result of the iterative calculation.

[0205] In implementation, the preset threshold can be set according to the positioning accuracy requirements, for example, 0.5. During the iterative calculation process, the calculation error of each candidate coordinate is continuously monitored. When the calculation error of a candidate coordinate is 0.4, which is less than the preset threshold of 0.5, it means that the coordinate has met the accuracy requirements. The coordinate (e.g., (3.2, 2.1, 1.6)) is then output as the optimal spatial coordinate of the discharge point.

[0206] In detail, the step of calculating the sound wave propagation time correction value based on the signal delay difference includes: the time correction value is a value that adjusts the sound wave propagation time based on the signal delay difference, and it is used to correct the deviation in sound wave propagation time calculation caused by various factors.

[0207] In practice, the signal delay difference is 2 milliseconds. Since the propagation time of the current signal is extremely short and negligible, the actual propagation time of the sound wave should be the signal delay difference plus other possible time deviations. Assuming that the time correction value is 0.5 milliseconds after analysis (this is just an example, and the actual calculation needs to be based on the specific situation).

[0208] Specifically, the step of multiplying the time correction value by the sound velocity based on the air medium inside the switchgear to obtain the distance correction value includes:

[0209] The distance correction value is a numerical value used to correct the equivalent propagation distance, calculated using the time correction value and the speed of sound. The speed of sound in air is the speed at which sound waves propagate in the air inside the switch cabinet, and in this invention, it is taken as 346 meters per second.

[0210] In implementation, given a time correction value of 0.5 milliseconds (i.e., 0.0005 seconds) and a sound speed of 346 meters per second, the distance correction value = time correction value × sound speed = 0.0005 × 346 = 0.173 meters.

[0211] Specifically, the step of subtracting the distance correction value from the equivalent propagation distance to obtain the corrected actual propagation distance, wherein the corrected actual propagation distance serves as an input parameter for the iterative solution of the optimization algorithm, including:

[0212] The corrected actual propagation distance refers to the equivalent propagation distance after adjustment by the distance correction value, which is closer to the true propagation distance of sound waves. Input parameters refer to the data needed during the iterative solution process of the optimization algorithm; the corrected actual propagation distance is used to adjust distance constraints, etc.

[0213] In practice, the equivalent propagation distance is 4 meters, and the distance correction value is 0.173 meters. Therefore, the corrected actual propagation distance is 4 - 0.173 = 3.827 meters. This distance is used as the input parameter of the optimization algorithm to update the distance constraints. For example, the distance constraint from the discharge point to the ultrasonic sensor is adjusted to 3.827 meters.

[0214] The corrected steps improved the accuracy of the equivalent propagation distance and resolved the problem of decreased positioning accuracy caused by deviations in propagation distance calculation.

[0215] In summary, this step, through a series of operations including defining the area, establishing constraints, and iterative optimization, ultimately solves for the optimal spatial coordinates of the discharge point. Specifically, the particle swarm optimization algorithm is used for iterative solving, combined with distance constraints and correction mechanisms, to efficiently and accurately locate the discharge point coordinates, overcoming the shortcomings of traditional positioning methods such as low accuracy and poor efficiency.

[0216] S6. Map the optimal spatial coordinates to the switch cabinet structure topology diagram to generate a partial discharge location report for the electrical equipment.

[0217] In this embodiment of the invention, mapping the optimal spatial coordinates to the switchgear structural topology diagram and generating a partial discharge location report for the electrical equipment includes:

[0218] The optimal spatial coordinates are converted into two-dimensional coordinates in the switch cabinet structure topology diagram;

[0219] The internal components of the switchgear are marked with coordinates, and the internal components of the switchgear include busbars, insulators and circuit breakers;

[0220] The frequency and intensity of discharge points within a preset time period are statistically analyzed.

[0221] A location report is generated by combining the component attributes of the internal components of the switch cabinet, including the location, discharge intensity, and potential fault type.

[0222] In detail, the step of mapping the optimal spatial coordinates to the switchgear structural topology diagram and generating a partial discharge location report for the electrical equipment includes:

[0223] Optimal spatial coordinates refer to the three-dimensional coordinates of the discharge point obtained through iterative optimization algorithms. A switchgear structural topology diagram is a two-dimensional schematic diagram showing the layout and connection relationships of various components within the switchgear. A partial discharge location report is a document containing the location of the discharge point, related component information, and potential faults. Mapping is the process of transforming the three-dimensional optimal spatial coordinates onto a two-dimensional topology diagram. The resulting report visually presents relevant information about partial discharges, providing a basis for equipment maintenance.

[0224] Specifically, converting the optimal spatial coordinates into two-dimensional coordinates in the switch cabinet structural topology diagram includes:

[0225] Two-dimensional coordinates refer to the coordinates used to represent positions on the plane of the switch cabinet structural topology diagram, typically consisting of values ​​in both the horizontal and vertical dimensions. Transformation is the process of mapping the optimal three-dimensional spatial coordinates onto the two-dimensional topology diagram according to certain rules.

[0226] During implementation, the optimal spatial coordinates of the discharge point are known to be (3.2, 2.1, 1.6). The switchgear structural topology diagram uses the bottom surface of the switchgear as the projection plane, establishing a two-dimensional coordinate system with the horizontal axis as the X-axis and the vertical axis as the Y-axis. During conversion, the Z-axis coordinate is ignored (or based on the height corresponding to different areas of the topology diagram), and the X and Y values ​​of the three-dimensional coordinates are directly mapped to the X and Y axes of the topology diagram, for example, (3.2, 2.1). After scaling with the topology diagram (assuming the topology...),... Figure 1 (Centimeters represent 0.1 meters in reality), resulting in two-dimensional coordinates on the topological map of (32 cm, 21 cm).

[0227] Specifically, the internal components of the switchgear corresponding to the marked coordinates, including busbars, insulators, and circuit breakers, include:

[0228] The markings are made at two-dimensional coordinate positions on the switchgear structural topology diagram to indicate the location of the discharge point. Internal components of the switchgear refer to the electrical parts installed inside the switchgear; busbars are conductors used to transmit electrical energy, insulators are components that provide insulation, and circuit breakers are devices used to open or close circuits.

[0229] During implementation, the location corresponding to the two-dimensional coordinates (32 cm, 21 cm) on the topology map is found. By checking the component layout corresponding to that location, it is determined that the location belongs to the vicinity of the bus. Therefore, the "discharge point" is marked at that coordinate on the topology map, and the corresponding component is noted as the bus.

[0230] This step clarifies the components associated with the discharge point, solving the problem of not being able to perform targeted maintenance because the corresponding components of the discharge point are unknown.

[0231] Specifically, the frequency and intensity of the statistical discharge points within a preset time period include:

[0232] The preset time refers to a pre-defined period of time for statistical analysis of discharge events, such as one hour. The frequency of occurrence refers to the number of times a partial discharge occurs at the discharge point within the preset time. The discharge intensity refers to the strength of the partial discharge, which is usually reflected by parameters such as the amplitude of the current pulse sequence. Statistical analysis is the process of recording and calculating the frequency and intensity.

[0233] In implementation, a preset time period of 1 hour is set, and the discharge status of the discharge point within this time period is recorded by monitoring equipment. Assuming that 5 partial discharges occur at the discharge point within 1 hour, the discharge intensity is judged to be moderate by analyzing the peak amplitude of the current pulse sequence, and these data are statistically analyzed.

[0234] This step obtains information on the activity patterns and intensity of the discharge points, solving the problem of being unable to assess the severity of the fault due to a lack of discharge frequency and intensity data. The previous steps determined the location of the discharge points, and this step is based on that location to conduct targeted statistics. Without a clear location, the statistics would lose their target.

[0235] In detail, the step of generating a location report that includes the location, discharge intensity, and potential fault type by combining the component attributes of the internal components of the switchgear includes:

[0236] Component attributes refer to the characteristics of components inside the switchgear, such as the material of the busbars and the insulation class of the insulators. Location refers to the position of the discharge point on the switchgear's structural topology diagram. Potential fault types are possible faults inferred based on the discharge point location, component attributes, and discharge intensity, such as insulation aging and poor contact. Report generation is the process of organizing the above information into a standardized document.

[0237] During implementation, it was known that the discharge point was located near the busbar, the discharge intensity was medium, and the busbar components were copper with a rated current of 500A. Based on this information, it was deduced that the potential fault type might be partial discharge caused by damage to the busbar insulation layer. The location (two-dimensional coordinates on the topology diagram and corresponding components), discharge intensity (medium), and potential fault type (damage to the busbar insulation layer) were compiled into a document to form a partial discharge location report.

[0238] In summary, this step, through coordinate transformation, component marking, data statistics, and report generation, completes the final presentation of partial discharge location. Among these steps, inferring potential fault types by combining component attributes—linking discharge information with component characteristics—enhances the report's practical value and provides precise guidance for equipment maintenance.

[0239] In the several embodiments provided by this invention, it should be understood that the disclosed method can be implemented in other ways.

[0240] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0241] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, and technology that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0242] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for locating and detecting partial discharge in electrical equipment, characterized in that, The method includes: S1. By connecting the grounding lead of the switchgear to the pulse current sensor and attaching the ultrasonic sensor to the insulating baffle of the switchgear, a synchronous current pulse sequence and ultrasonic wave are generated. S2. Based on the current pulse sequence and the ultrasonic waveform, calculate the signal delay difference between the grounding lead and the sensor at the insulating baffle; S3. Based on the three-dimensional structure of the switchgear's metal cavity and the sensor layout coordinates, establish a multi-path acoustic wave propagation database containing direct paths and desired reflection paths, including: Measure the inner wall dimensions, corner angles, and positions of insulating baffles of the switchgear metal cavity, and construct a three-dimensional structural model; Mark the layout coordinates of the pulse current sensor and the ultrasonic sensor in the three-dimensional structural model to determine the straight-line distance between the sensors; Simulating the direct path of sound waves from the discharge point to the ultrasonic sensor, and recording the path length and propagation medium properties, includes: setting a set of virtual discharge points in the three-dimensional structural model, the set of virtual discharge points covering the possible discharge area of ​​the switch cabinet metal cavity; for each virtual discharge point, generating a straight propagation trajectory from the virtual discharge point to the ultrasonic sensor as the direct path; and recording the path length of the straight propagation trajectory and the sound speed characteristics of the propagation medium. Simulate the desired reflection path of sound waves after reflection from the metal cavity wall and insulating baffle, and record the number of reflections, the coordinates of the reflection point, and the path length; The parameters of the direct path and the desired reflection path are summarized to establish a multipath database for sound wave propagation; S4. Match the first arriving wave feature identified in the ultrasonic wave pattern with the sound wave propagation multipath database to determine the actual sound wave propagation path type and the corresponding equivalent propagation distance, including: The peak amplitude, rise slope, and waveform duration of the first arriving wave are extracted from the ultrasonic waveform as characteristic parameters of the arriving wave. Call the theoretical waveform characteristic parameters corresponding to each path in the sound wave propagation multipath database; Calculate the similarity between the characteristic parameters of the first arriving wave and the characteristic parameters of each theoretical waveform; Based on the path corresponding to the theoretical waveform with the highest similarity, the actual sound wave propagation path type and equivalent propagation distance are determined. S5. Combining the signal delay difference, the sensor deployment coordinates, and the equivalent propagation distance, the optimal spatial coordinates of the discharge point are determined iteratively through an optimization algorithm. S6. Map the optimal spatial coordinates to the switch cabinet structure topology diagram to generate a partial discharge location report for the electrical equipment.

2. The method for locating and detecting partial discharge in electrical equipment as described in claim 1, characterized in that, The process involves connecting a pulse current sensor to the grounding lead of the switchgear, and an ultrasonic sensor abutting the insulating baffle of the switchgear to generate a synchronized current pulse sequence and ultrasonic wave pattern, including: The high-frequency current signal in the grounding lead is collected by a pulse current sensor and then filtered to generate a standardized current pulse sequence. The ultrasonic sensor receives the acoustic wave signal inside the switch cabinet, and generates an ultrasonic wave after noise suppression processing. A time synchronization device is used to clock-align the current pulse sequence with the ultrasonic wave pattern.

3. The method for locating and detecting partial discharge in electrical equipment as described in claim 1, characterized in that, The calculation of the signal delay difference between the grounding lead and the sensor at the insulating baffle based on the current pulse sequence and the ultrasonic waveform includes: The peak time of the first pulse in the current pulse sequence is extracted as the reference time; Identify the starting fluctuation point in the ultrasonic wave pattern that corresponds to the reference time; Calculate the time difference between the reference time and the starting fluctuation point, and use it as the initial time delay difference.

4. The method for locating and detecting partial discharge in electrical equipment as described in claim 1, characterized in that, The step of combining the signal delay difference, the sensor deployment coordinates, and the equivalent propagation distance to iteratively determine the optimal spatial coordinates of the discharge point through an optimization algorithm includes: Using the layout coordinates of the pulse current sensor and the ultrasonic sensor as boundary points, a cubic space including the line connecting the two and the surrounding area is delineated as the initial spatial coordinate range of the discharge point. The distance constraint between the discharge point and the two sensors is determined based on the signal delay difference and the equivalent propagation distance. Based on the aforementioned distance constraints, an objective function is constructed with the spatial coordinates of the discharge point as the variable. The output value of the objective function is the sum of the deviations from the distance constraints. The objective function is calculated iteratively using a particle swarm optimization algorithm, and the candidate coordinates of the discharge point are updated in each iteration; When the calculation error of the candidate coordinates is less than a preset threshold, the candidate coordinates are output as the optimal spatial coordinates.

5. The method for locating and detecting partial discharge in electrical equipment as described in claim 4, characterized in that, The step of iteratively calculating the objective function using a particle swarm optimization algorithm, updating the candidate coordinates of the discharge point in each iteration, includes: Initialize the particle positions of the particle swarm, with each particle corresponding to a candidate coordinate of the discharge point, and the particle positions are distributed within the range of the initial spatial coordinates; Using the output value of the objective function as the fitness, the particle velocity and position are updated through a particle swarm optimization algorithm to iteratively optimize the candidate coordinates; Calculate the objective function output value corresponding to the candidate coordinates after each iteration, and use this output value as the calculation error.

6. The method for locating and detecting partial discharge in electrical equipment as described in claim 4, characterized in that, The signal delay difference is used to correct the equivalent propagation distance, specifically including: Calculate the time correction value for sound wave propagation based on the signal delay difference; Based on the sound velocity of the air medium inside the switch cabinet, the time correction value is multiplied by the sound velocity to obtain the distance correction value; The corrected actual propagation distance is obtained by subtracting the distance correction value from the equivalent propagation distance, wherein the corrected actual propagation distance is used as the input parameter for the optimization algorithm to solve iteratively.

7. The method for locating and detecting partial discharge in electrical equipment as described in claim 1, characterized in that, The step of mapping the optimal spatial coordinates to the switchgear structural topology diagram and generating a partial discharge location report for the electrical equipment includes: The optimal spatial coordinates are converted into two-dimensional coordinates in the switch cabinet structure topology diagram; The internal components of the switchgear are marked with coordinates, and the internal components of the switchgear include busbars, insulators and circuit breakers; The frequency and intensity of discharge points within a preset time period are statistically analyzed. A location report is generated by combining the component attributes of the internal components of the switch cabinet, including the location, discharge intensity, and potential fault type.

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