Partial discharge detection and positioning method and system based on fluorescent optical fiber

Abstract

The embodiment of the invention provides a partial discharge detection and positioning method and system based on a fluorescent optical fiber. The method is applied to the technical field of discharge detection and positioning, and comprises the following steps: when local discharge occurs, photons are coupled into an optical fiber by a capture field to form an initial photon flow; synchronously monitoring the arrival time of photons at the two ends of the optical fiber through a photomultiplier, and converting each photon flow into time sequence data which is a time mark sequence; the position mapping algorithm is based on the constancy of the photon propagation speed in the optical fiber and the correlation of the time stamp sequence, firstly, the time difference is converted into a relative distance parameter, then the geometric layout of the optical fiber is matched through iterative optimization, and finally, a discharge position coordinate is generated; the output is the three-dimensional space coordinates of the partial discharge point. In this way, the technical problems that in the prior art, photon capturing efficiency is low, time synchronization precision is insufficient, and space positioning is fuzzy can be solved.

Description

Technical Field

[0001] This invention relates to the field of discharge detection and localization technology, and in particular to a method and system for partial discharge detection and localization based on fluorescent optical fiber. Background Technology

[0002] Partial discharge (PD) caused by insulation defects in power equipment is like a hidden lesion in the power system. Traditional detection methods are like using a stethoscope to diagnose complex organ diseases: (1) Although the pulse current method is an IEC standard, it requires power outage and connection of coupling capacitor, which is like performing a puncture biopsy on a running heart; (2) Although the ultra-high frequency (UHF) method can achieve non-contact detection, electromagnetic waves will produce an "echo labyrinth" effect in the metal enclosed structure, and the positioning error in GIS equipment often exceeds 1.5 meters; (3) The ultrasonic method is easily affected by mechanical vibration and noise interference, and the signal-to-noise ratio at the substation site is often less than 3dB. In typical discharge scenarios such as transformer oil gaps and cable terminals, these methods are like looking for flowers in the fog - you can see the phenomenon, but you can't find the root cause.

[0003] Existing fiber optic acoustic wave sensing technology uses a Fabry-Perot interferometer to detect discharge acoustic emissions. However, this is like trying to observe ocean waves under a microscope; high-frequency sound waves above -40kHz attenuate by up to 8dB / cm in oil-paper insulation, and it cannot distinguish between mechanical vibrations and discharge pulses. Fluorescence lifetime thermometry locates hotspots through the temperature response of rare-earth fluorescent materials, but the transient temperature rise caused by discharge is only 0.1-2K, like trying to measure the temperature of lightning with a thermometer. Distributed fiber optic sensing, based on a Φ-OTDR vibration detection system, has a 5-meter spatial resolution for vibrations <1cm. 3 Discharging power is like using a satellite map to find an ant hole.

[0004] Existing solutions have limitations such as being unable to capture the leading edge of nanosecond-level discharge pulses, implying a theoretical positioning limit of 50cm for a 300MHz signal, the inability of a single physical quantity detection—acoustic signal—to reflect the discharge intensity, difficulty in positioning with electromagnetic signals, and minute-level lag in temperature field changes. Summary of the Invention

[0005] This invention provides a method and system for partial discharge detection and localization based on fluorescent optical fiber, which solves the technical problems of low photon capture efficiency, insufficient time synchronization accuracy and ambiguous spatial positioning in the prior art.

[0006] According to a first aspect of the present invention, a method for partial discharge detection and localization based on fluorescent optical fiber is provided, comprising: When partial discharge occurs, photons are coupled into the fiber by the trapping field, forming an initial photon flow. The photon trapping field originates from the microstructure modification of the fluorescent fiber, that is, a nonlinear optical coating is prepared on the fiber surface. This coating is composed of fluorescent materials of a specific wavelength, which can actively attract and trap photons, thereby improving the efficiency of photons entering the fiber.

[0007] The initial photon stream propagates along the fluorescent fiber and is processed through a time-stamping process. The time-stamping process utilizes the dispersion characteristics of the fiber and the interaction between photons and fluorescent materials to implant a unique time signature into the photon stream. The arrival time of photons is synchronously monitored at both ends of the fiber by photomultiplier tubes. Each photon stream is converted into time series data, which is a time-stamped sequence containing the precise time difference information of the photons arriving at the sensors at both ends.

[0008] The time-stamped sequence is used to analyze the time difference and calculate the location of partial discharge through a position mapping algorithm. The position mapping algorithm is based on the constancy of photon propagation speed in optical fiber and the correlation of time-stamped sequence. First, the time difference is converted into a relative distance parameter. Then, the geometric layout of the matching optical fiber is iteratively optimized to finally generate the discharge position coordinates. The discharge position coordinates directly depend on the accuracy of the time-stamped sequence, achieving high-precision positioning. The output is the three-dimensional spatial coordinates of the partial discharge point, completing the entire detection and positioning process.

[0009] According to a second aspect of the present invention, a partial discharge detection and localization system based on fluorescent optical fiber is provided, comprising: The photon trapping module is used to couple photons into the interior of the optical fiber by the trapping field when a local discharge occurs, forming an initial photon flow. The photon stream conversion module is used to process the initial photon stream propagating along the fluorescent fiber through a time stamp embedding process. The time stamp embedding utilizes the dispersion characteristics of the fiber and the interaction between photons and fluorescent materials to implant a unique time signature into the photon stream. The arrival time of photons is synchronously monitored at both ends of the fiber by photomultiplier tubes. Each photon stream is converted into time series data, which is a time stamp sequence containing the precise time difference information of the photons arriving at the sensors at both ends. The position mapping module is used to analyze the time difference of the time stamp sequence and calculate the location of partial discharge through the position mapping algorithm. Based on the constancy of photon propagation speed in optical fiber and the correlation of time stamp sequence, the time difference is first converted into a relative distance parameter. Then, the geometric layout of the matching optical fiber is iteratively optimized to finally generate the discharge position coordinates. The output is the three-dimensional spatial coordinates of the partial discharge point.

[0010] Compared with existing technologies, the advantages and positive effects of this invention are: This invention improves signal quality and temporal resolution. The coating on the fluorescent fiber enhances photon capture efficiency, ensuring sufficient initial signal strength. Time stamp embedding, combined with simultaneous monitoring at both ends, converts the photon stream into high-precision time-series data, providing reliable input for subsequent positioning. High-precision spatiotemporal mapping directly inputs the time difference information of the time-stamped sequence into the position mapping algorithm. Through the constancy of photon propagation speed and matching of fiber geometry, the time difference is converted into precise spatial coordinates, achieving three-dimensional positioning. End-to-end detection and positioning optimization, with initial signal enhancement, high-precision time synchronization, and spatial coordinate calculation forming a closed-loop detection process, achieves this. Compared to traditional methods (such as the UHF method relying on electromagnetic wave propagation and the acoustic method being affected by medium attenuation), active photon capture and time stamping based on fluorescent fiber achieve more stable and higher-precision partial discharge detection and positioning.

[0011] It should be understood that the description in the Summary of the Invention is not intended to limit the key or essential features of the embodiments of the present invention, nor is it intended to restrict the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0012] The above and other features, advantages, and aspects of the various embodiments of the present invention will become more apparent from the accompanying drawings and the following detailed description. The drawings are provided for a better understanding of the invention and are not intended to limit the invention. In the drawings, the same or similar reference numerals denote the same or similar elements, wherein: Figure 1 A flowchart of a partial discharge detection and localization method based on fluorescent optical fiber according to an embodiment of the present invention is shown; Figure 2 A block diagram of a partial discharge detection and localization system based on fluorescent optical fiber according to an embodiment of the present invention is shown; Figure 3 A block diagram of an exemplary electronic device capable of implementing embodiments of the present invention is shown. Detailed Implementation

[0013] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0014] Furthermore, the term "and / or" in this invention is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this invention generally indicates that the preceding and following related objects have an "or" relationship.

[0015] Figure 1 A schematic flowchart of a partial discharge detection and localization method 100 based on fluorescent optical fiber according to an embodiment of the present invention is shown, as follows: Figure 1 As shown, method 100 includes: S110: When a local discharge occurs, photons are coupled into the fiber by the trapping field, forming an initial photon flow. The photon trapping field originates from the microstructure modification of the fluorescent fiber, that is, a nonlinear optical coating is prepared on the surface of the fiber. This coating is composed of fluorescent materials of a specific wavelength, which can actively attract and trap photons, thereby improving the efficiency of photons entering the fiber.

[0016] Optionally, in some embodiments, the process of forming the initial photon stream specifically includes the following steps: S111: When a local discharge event occurs, the discrete photons radiated in space interact with the nonlinear optical coating on the surface of the fluorescent fiber; the nonlinear optical coating can resonate with the energy of the local discharge photons; the resonant absorption triggers the nonlinear optical response of the coating, which manifests as the instantaneous generation of a microscale high-gradient electromagnetic field at the photon incident point. This field is defined as the photon trapping field.

[0017] S112: The photon trapping field acts on the incident photon as a directional energy funnel effect. Through the spatial distribution of its gradient, it modulates the momentum of the photon, overcomes its original random motion direction, and converts its kinetic energy into directional motion pointing towards the fiber core. The momentum-modulated photon is efficiently injected into the transmission medium of the fiber, completing the state transition from free space radiation to waveguide-constrained propagation.

[0018] S113: A large number of photons are injected into the transmission medium in sequence. Their individual behavior exhibits the consistency of the group under the synchronous modulation of the photon trapping field. This is manifested as the high concentration of the photon group in the transmission axis and the high synchronization of the initial phase, which converges into a photon set with a clear transmission direction and close time correlation, namely the initial photon stream. The formation of the initial photon stream provides a signal carrier with good temporal and spatial characteristics for subsequent processing.

[0019] S120: The initial photon stream propagates along the fluorescent fiber and is processed through a time-stamping process. The time-stamping process utilizes the dispersion characteristics of the fiber and the interaction between photons and fluorescent materials to implant a unique time signature into the photon stream. The arrival time of photons is synchronously monitored at both ends of the fiber by photomultiplier tubes. Each photon stream is converted into time series data, which is a time-stamped sequence containing the precise time difference information of the photons arriving at the sensors at both ends.

[0020] Optionally, in some embodiments, the process of synchronously monitoring the arrival time of photons at both ends of the optical fiber using photomultiplier tubes specifically includes the following steps: S121: The initial photon stream in transmission enters the time signature embedding stage, utilizing the inherent dispersion characteristics of optical fiber materials, namely the difference in propagation speed of photons of different wavelengths; by pre-managing the dispersion of the optical fiber to give it a specific nonlinear dispersion profile, when the initial photon stream passes through this profile, photons of different wavelengths inside it will generate controllable, nonlinear velocity differentiation; differentiation causes the photon stream to be actively stretched and modulated in the time domain, rather than passively broadened, thereby implanting a unique waveform distortion determined by the dispersion characteristics and related to the propagation distance into the overall structure of the photon group, which constitutes the time signature of the photon.

[0021] S122: The photon stream carrying the time signature then arrives at both ends of the optical fiber and is received by the high-sensitivity optical sensors at both ends; the high-sensitivity optical sensors perform a synchronous photon event detection based on a common clock reference, and the sensors at both ends mark each arriving photon event, i.e., the individual manifestation of the time signature, with high precision and record its absolute arrival time.

[0022] S123: The set of timestamps continuously recorded by each sensor forms two original asynchronous arrival sequences; the two original asynchronous arrival sequences are input into a bidirectional sequence correlator; the bidirectional sequence correlator performs cross-correlation calculation based on the similarity waveforms of the timestamps in the two sequences; by identifying and matching the consistent waveform features generated by the same initial photon stream in the two sequences, the bidirectional sequence correlator can accurately match the same photon event captured by the two sensors and filter out background noise photon events.

[0023] In this embodiment of the invention, step S123, in which the bidirectional sequence correlator performs cross-correlation calculation based on the similarity waveforms of the time signatures in the two sequences, specifically includes the following steps: S1231: The bidirectional sequence correlator extracts waveform feature segments from two asynchronous arrival sequences. Centered on each timestamp in the two asynchronous arrival sequences, it extracts a very short time window and transforms the densely distributed discrete photon event timestamps within the time window into a continuous digital waveform with a specific undulating shape. The digital waveform is the electrical signal representation of the time signature at the sensor end. Its shape is uniquely determined by the waveform distortion implanted in the previous time mark embedding process. Therefore, photon events originating from the same initial photon stream will have highly similar waveform shapes on both sensors.

[0024] S1232: Start the consensus kernel calculation; perform a nonlinear transformation on a waveform feature segment extracted from one of the asynchronous arrival sequences to enhance the unique features in the waveform determined by the time signature, while suppressing the common noise background. The generated consensus kernel is then matched with the waveforms in all possible time windows of another asynchronous arrival sequence for feature resonance matching.

[0025] S1233: Feature resonance matching outputs a set of resonance intensity coefficients. Each resonance intensity coefficient represents the degree of matching between the waveform at a specific position in the asynchronous arrival sequence and the consistency kernel. When the operation scans to the waveform segment in the asynchronous arrival sequence that was generated by the same initial photon stream, its unique shape will generate an extremely high resonance intensity coefficient with the consistency kernel, forming a significant correlation peak.

[0026] S1234: By detecting the correlation peak that exceeds the preset threshold, the bidirectional sequence correlator can complete the precise photon event pairing; the pairing successfully associates a specific timestamp in the asynchronous arrival sequence at different ends with a timestamp caused by the same group of photons, and automatically rejects spurious event pairings that cannot form high resonance intensity and are caused by background noise or different photon streams; finally, the result of each successful precise photon event pairing is output as a pair of highly correlated timestamps, providing precise input for the next step of generating absolute time difference data points.

[0027] S124: For each pair of successfully paired photon events, the bidirectional sequence correlator obtains the difference between its two timestamps and generates an absolute time difference data point; the time difference data points generated by all successfully paired photon events within the entire detection window are arranged in chronological order to finally generate a time stamp sequence that can be used for precise positioning; each data point in this sequence is directly derived from the time signature implanted in the time stamp embedding process, and its accuracy directly determines the accuracy of subsequent positioning calculations.

[0028] S130: The time-stamped sequence is used to analyze the time difference and calculate the location of the partial discharge through a position mapping algorithm. The position mapping algorithm is based on the constancy of photon propagation speed in the optical fiber and the correlation of the time-stamped sequence. First, the time difference is converted into a relative distance parameter. Then, the geometric layout of the matching optical fiber is iteratively optimized to finally generate the discharge position coordinates. The discharge position coordinates directly depend on the accuracy of the time-stamped sequence, achieving high-precision positioning. The output is the three-dimensional spatial coordinates of the partial discharge point, completing the entire detection and positioning process.

[0029] Optionally, in some embodiments, the position mapping algorithm is based on the process of the constancy of photon propagation speed in the optical fiber and the correlation of time-stamped sequences, specifically including the following steps: S131: First, perform relative distance parameter conversion, multiply each time difference data point in the time stamp sequence by the group velocity constant, convert the time difference dimension to the length dimension, and generate a primary distance difference; the primary distance difference represents the difference in physical path length between the discharge point and the sensors at both ends of the optical fiber.

[0030] S132: Substituting the primary distance difference into a spatial projection operator, the one-dimensional scalar distance difference is mapped onto a three-dimensional spatial curve defined by the fiber optic geometric layout model. The projection process calculates the set of all possible points on the three-dimensional model curve that satisfy this primary distance difference condition; this set of possible points is called the candidate location point cloud. The construction of the fiber optic geometric layout model originates from the refined three-dimensional scanning of the internal space of the device under test and the precise digitization of the fiber optic laying path. This process uses laser mapping technology to acquire spatial point cloud data of the internal structure of switchgear, combined electrical appliances, or transformers. In this digital space, the actual laying trajectory of the fluorescent fiber is represented as a continuous three-dimensional spatial parameter curve. The mathematical expression of this curve provides the geometric reference for subsequent projection and calculation.

[0031] S133: In the candidate location point cloud, the attenuation process of photons propagating from each candidate point to both ends is simulated, and the simulation results are matched with the photon flow intensity data received by the actual sensors at both ends. Through continuous iteration, the candidate point that minimizes the matching error between the simulated attenuation data and the measured intensity data is found. When the error value is lower than the threshold set by the consistency convergence criterion, the iteration terminates. Finally, the three-dimensional coordinates of the unique candidate point that satisfies the consistency convergence criterion are output by the algorithm, which is the final discharge location coordinate.

[0032] The process of matching the simulation results with the actual photon flux intensity data received by the sensors at both ends includes the following steps: S1331: Using the spatial coordinates of the candidate point as input, calculate the theoretical signal attenuation that the initial photon stream should experience as it propagates from that point to the sensors at both ends of the optical fiber, and output a pair of simulated attenuation values.

[0033] S1332: Compare a pair of simulated attenuation values ​​with a pair of photon flow intensity data actually collected by the sensor. Based on the spectral similarity measure of the signal energy distribution pattern, the spectral similarity measure generates a fidelity coefficient by calculating the covariance matrix of the simulated and measured data on specific frequency domain features, which is used to quantify the degree of consistency between the two in terms of energy attenuation pattern.

[0034] S1333: The fidelity coefficient is used to drive the optimal solution search process. Based on the adaptive convergence criterion, the high-confidence subset of points with the highest fidelity coefficient is continuously screened through multiple rounds of iteration, and the grid around it is refined to generate a new generation of candidate point clouds until the coefficient variance is lower than the threshold. Finally, the coordinates of the center point of the convergence region are output as the discharge position coordinates.

[0035] The process of continuously selecting the high-confidence subset of points with the highest fidelity coefficient through multiple rounds of iteration includes the following steps: S13331: The iterative optimization process guided by the adaptive convergence criterion begins with the candidate point cloud of the current generation and its corresponding set of fidelity coefficients; all fidelity coefficients are sorted by statistical significance and arranged in descending order according to the magnitude of the coefficient values ​​to determine the confidence level of each candidate point in space.

[0036] S13332: The statistically significant sequence is input into a spatial confidence region construction process. A certain number of candidate points with the highest ranking are selected. High-fidelity points often form several clustered regions in space. By obtaining the spatial distribution characteristics of high-fidelity points, one or more three-dimensional confidence ellipsoids are constructed. The spatial position and semi-axis length of the confidence ellipsoid are jointly determined by the coordinates of the candidate points contained within it and the weight of their fidelity coefficients. The confidence ellipsoid defines the potential spatial range of the next generation search. According to the accuracy improvement requirements specified by the adaptive convergence criterion, new nodes are uniformly distributed within the confidence ellipsoid with a grid resolution much higher than that of the previous generation. The set of these new nodes constitutes the next generation candidate location point cloud.

[0037] The process of constructing a new generation of candidate location point clouds specifically includes the following steps: S133321: The geometric parameters of the confidence ellipsoid and the adaptive convergence criterion are input into a structural adaptive grid. The structural adaptive grid is generated based on the three principal axis directions of the confidence ellipsoid and the length of its semi-axis, thus parameterizing the interior space of the ellipsoid.

[0038] S133322: Apply the node density modulation function, input the spatial coordinates of any point within the ellipsoid, and output the theoretical node density at that point.

[0039] The process of applying the node density modulation function includes the following steps: S1333221: Given the spatial coordinates of any point within the ellipsoid, perform an affine transformation to map it to the unit sphere parameter space. This transformation is based on the three principal axes of the ellipsoid and the lengths of its semi-axis, ensuring that ellipsoids of different shapes can be converted into a standard reference system for easier subsequent calculations.

[0040] S1333222: Unit sphere parameter space input density modulation function, which consists of three core components: Radial density attenuation component: Along the principal axis of the ellipsoid, the node density decreases exponentially, ensuring sparse sampling points near the edge; Local curvature sensitive component: Based on the differences in the semi-axis lengths along each axis of the ellipsoid, the density distribution is dynamically adjusted, and the sampling density is automatically increased in high curvature regions (short semi-axis direction); Historical iteration correction component: Combining the node distribution errors of the previous iteration, feedback adjustment is applied to optimize the smoothness and continuity of the current density field.

[0041] S1333223: The obtained initial density value is truncated by upper and lower bounds to ensure that it falls within a preset reasonable range; the final output is the theoretical node density of the point in the current ellipsoid space, which will be used for subsequent node coordinate generation.

[0042] S133323: Within the parameterized ellipsoidal space, the three-dimensional coordinates of each new node are calculated according to the density distribution calculated by the node density modulation function; the set of coordinates of these new nodes constitutes the next generation of candidate location point cloud.

[0043] S13333: The new generation of candidate location point clouds is sent back to the previous process for attenuation simulation and fidelity calculation, starting a new iterative cycle. As the number of iterations increases, the range of the confidence ellipsoid continues to shrink, and the density of its internal grid nodes continues to increase. When the statistical variance of the fidelity coefficients of all candidate points in the latest generation is lower than the preset threshold, the adaptive convergence criterion determines that the optimization is complete. The coordinates of all points in the final generation of candidate location point clouds are calculated by weighted average, with the weight being the corresponding fidelity coefficient, thereby outputting the final discharge location coordinates and completing the transformation from probabilistic point clouds to deterministic coordinates.

[0044] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, because according to the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0045] The above is an introduction to the method embodiments. The following describes the solution of the present invention further through device embodiments.

[0046] Figure 2 A block diagram of a partial discharge detection and localization system 200 based on fluorescent optical fiber according to an embodiment of the present invention is shown. Figure 2 As shown, system 200 includes: The photon trapping module 210 is used to couple photons into the interior of the optical fiber by the trapping field when a local discharge occurs, forming an initial photon flow. The photon trapping field originates from the microstructure modification of the fluorescent optical fiber, that is, a nonlinear optical coating is prepared on the surface of the optical fiber. This coating is composed of fluorescent materials of a specific wavelength, which can actively attract and trap photons, thereby improving the efficiency of photons entering the optical fiber.

[0047] The photon stream conversion module 220 is used to process the initial photon stream as it propagates along the fluorescent optical fiber. The time stamp embedding process utilizes the dispersion characteristics of the optical fiber and the interaction between photons and fluorescent materials to implant a unique time signature into the photon stream. The arrival time of photons is synchronously monitored at both ends of the optical fiber by photomultiplier tubes. Each photon stream is converted into time series data, which is a time stamp sequence containing the precise time difference information of the photons arriving at the sensors at both ends.

[0048] The position mapping module 230 is used to analyze the time difference of the time stamp sequence and calculate the location of partial discharge through the position mapping algorithm. The position mapping algorithm is based on the constancy of photon propagation speed in optical fiber and the correlation of time stamp sequence. First, the time difference is converted into a relative distance parameter. Then, the geometric layout of the matching optical fiber is iteratively optimized to finally generate the discharge position coordinates. The discharge position coordinates directly depend on the accuracy of the time stamp sequence, realizing high-precision positioning. The output is the three-dimensional spatial coordinates of the partial discharge point, completing the entire detection and positioning process.

[0049] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the described module can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0050] According to embodiments of the present invention, the present invention also provides an electronic device and a readable storage medium.

[0051] Figure 3A schematic block diagram of an electronic device 300 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown in this invention, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0052] Electronic device 300 includes a computing unit 301, which can perform various appropriate actions and processes according to a computer program stored in ROM 302 or a computer program loaded into RAM 303 from storage unit 308. RAM 303 can also store various programs and data required for the operation of electronic device 300. The computing unit 301, ROM 302, and RAM 303 are interconnected via bus 304. I / O interface 305 is also connected to bus 304.

[0053] Multiple components in electronic device 300 are connected to I / O interface 305, including: input unit 306, such as keyboard, mouse, etc.; output unit 307, such as various types of displays, speakers, etc.; storage unit 308, such as disk, optical disk, etc.; and communication unit 309, such as network card, modem, wireless transceiver, etc. Communication unit 309 allows electronic device 300 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0054] The computing unit 301 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 301 performs the various methods and processes described above, such as the fluorescent fiber-based partial discharge detection and localization method. For example, in some embodiments, the fluorescent fiber-based partial discharge detection and localization method can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as storage unit 308. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 300 via ROM 302 and / or communication unit 309. When the computer program is loaded into RAM 303 and executed by the computing unit 301, one or more steps of the fluorescent fiber-based partial discharge detection and localization method described above can be performed. Alternatively, in other embodiments, the computing unit 301 may be configured to perform the fluorescent fiber-based partial discharge detection and localization method by any other suitable means (e.g., by means of firmware).

[0055] Various embodiments of the systems and techniques described above in this invention can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0056] The program code used to implement the methods of the present invention can be written in any combination of one or more programming languages. This program code can be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code can be executed entirely on the machine, partially on the machine, as a standalone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0057] In the context of this invention, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0058] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including voice input, speech input, or tactile input).

[0059] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0060] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0061] It should be understood that the various forms of processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this invention can be achieved, and this invention does not impose any limitations on them.

[0062] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for partial discharge detection and localization based on fluorescent optical fiber, characterized in that, include: The initial photon stream propagates along the fluorescent fiber and is processed through a time-stamping process. The arrival time of the photons is synchronously monitored at both ends of the fiber by photomultiplier tubes. Each photon stream is converted into time-series data, which is a time-stamped sequence containing the precise time difference information of the photons arriving at the sensors at both ends. The time-stamped sequence is used to parse the time difference and calculate the location of partial discharge through a position mapping algorithm. First, the time difference is converted into a relative distance parameter, and then the geometric layout of the matching fiber is iteratively optimized to finally generate the discharge location coordinates. The three-dimensional spatial coordinates of the partial discharge point are output.

2. The partial discharge detection and localization method based on fluorescent optical fiber according to claim 1, characterized in that, The process of synchronously monitoring the arrival time of photons at both ends of the optical fiber using photomultiplier tubes includes: The initial photon stream in transmission enters the time stamp embedding stage, which utilizes the inherent dispersion characteristics of optical fiber materials, namely the difference in the propagation speed of photons of different wavelengths; the optical fiber is pre-dispersion managed to have a nonlinear dispersion profile. When the initial photon stream passes through this profile, photons of different wavelengths inside it will generate controllable, nonlinear speed differentiation; waveform distortion is implanted into the overall structure of the photon group, which constitutes the time signature of the photons. The photon stream carrying the time signature then arrives at both ends of the optical fiber to perform synchronous photon event detection. Based on a common clock reference, the sensors at both ends timestamp each arriving photon event, i.e., the individual manifestation of the time signature, and record its absolute arrival time. The set of timestamps continuously recorded by each sensor forms two original asynchronous arrival sequences; cross-correlation is calculated based on the similarity waveforms of the timestamps in the two sequences; the same photon event captured by the sensors at both ends is matched by identifying and matching the consistent waveform features generated by the same initial photon stream in the two sequences. For each pair of successfully paired photon events, the bidirectional sequence correlator obtains the difference between its two timestamps to generate an absolute time difference data point; the time difference data points generated by all successfully paired photon events within the entire detection window are arranged in chronological order to generate a time-stamped sequence.

3. The partial discharge detection and localization method based on fluorescent optical fiber according to claim 1, characterized in that, The position mapping algorithm, based on the constancy of photon propagation speed in optical fiber and the correlation of time-stamped sequences, includes the following steps: First, a relative distance parameter transformation is performed. Each time difference data point in the time stamp sequence is multiplied by the group velocity constant to convert the time difference dimension into the length dimension, generating a primary distance difference. Substituting the primary distance difference into a spatial projection operator, the one-dimensional scalar distance difference is mapped onto a three-dimensional spatial curve defined by the fiber optic geometric layout model. The projection process calculates the set of all possible points on the three-dimensional model curve that satisfy the primary distance difference condition. The set of possible points is called the candidate location point cloud. In the candidate location point cloud, the attenuation process of photons propagating from each candidate point to both ends is simulated, and the simulation results are matched with the photon flow intensity data received by the actual sensors at both ends. Through continuous iteration, the candidate point that minimizes the matching error between the simulated attenuation data and the measured intensity data is found. When the error value is lower than the threshold set by the consistency convergence criterion, the iteration terminates. Finally, the three-dimensional coordinates of the unique candidate point that satisfies the consistency convergence criterion are output, which are the final discharge location coordinates.

4. The partial discharge detection and localization method based on fluorescent optical fiber according to claim 3, characterized in that, The process of matching the simulation results with the actual photon flux intensity data received by the sensors at both ends includes the following steps: Using the spatial coordinates of the candidate point as input, the theoretical signal attenuation that the initial photon stream should experience as it propagates from the candidate point to the sensors at both ends of the optical fiber is calculated, and a pair of simulated attenuation values ​​are output. A pair of simulated attenuation values ​​are compared with a pair of photon flow intensity data actually collected by the sensor. The spectral similarity measure is based on the signal energy distribution pattern. The spectral similarity measure generates a fidelity coefficient by calculating the covariance matrix of the simulated and measured data on specific frequency domain features. The fidelity coefficient is used to drive the optimal solution search process. Based on the adaptive convergence criterion, the high-confidence subset of points with the highest fidelity coefficient is continuously screened through multiple rounds of iteration, and the grid around it is refined to generate a new generation of candidate point clouds until the coefficient variance is lower than the threshold. Finally, the coordinates of the center point of the convergence region are output as the discharge position coordinates.

5. The partial discharge detection and localization method based on fluorescent optical fiber according to claim 4, characterized in that, The process of continuously selecting the high-confidence subset with the highest fidelity coefficient through multiple rounds of iteration includes the following steps: The iterative optimization process guided by the adaptive convergence criterion begins with the candidate point cloud of the current generation and its corresponding set of fidelity coefficients; all fidelity coefficients are sorted by statistical significance and arranged in descending order according to their numerical values ​​to determine the confidence level of each candidate point in space. The sequence sorted by statistical significance is input into a spatial confidence region construction process. The candidate points with the highest ranking are selected. High-fidelity points often form several clustered regions in space, constructing one or more three-dimensional confidence ellipsoids. New nodes are uniformly distributed inside the confidence ellipsoids, and the set of new nodes constitutes the next generation of candidate location point clouds. As the number of iterations increases, the range of the confidence ellipsoid continues to shrink, and the density of its internal grid nodes continuously increases; when the statistical variance of the fidelity coefficients of all candidate points in the latest generation is lower than the preset threshold, the adaptive convergence criterion determines that the optimization is complete; and the coordinates of all points in the final generation candidate location point cloud are calculated by weighted average.

6. The partial discharge detection and localization method based on fluorescent optical fiber according to claim 5, characterized in that, The process of constructing a new generation of candidate location point clouds includes the following steps: The geometric parameters of the confidence ellipsoid and the adaptive convergence criterion are input into a structural adaptive grid. The structural adaptive grid is generated based on the three principal axis directions of the confidence ellipsoid and their semi-axis lengths, thus parameterizing the interior space of the ellipsoid. By applying the node density modulation function and inputting the spatial coordinates of any point within the ellipsoid, the output is the theoretical node density at that point. Within the parameterized ellipsoidal space, the three-dimensional coordinates of each new node are calculated according to the density distribution calculated by the node density modulation function; the set of coordinates of these new nodes constitutes the next-generation candidate location point cloud.

7. The partial discharge detection and localization method based on fluorescent optical fiber according to claim 6, characterized in that, The process of constructing a new generation of candidate location point clouds includes the following steps: The geometric parameters of the confidence ellipsoid and the adaptive convergence criterion are input into a structural adaptive grid. The structural adaptive grid is generated based on the three principal axis directions of the confidence ellipsoid and their semi-axis lengths, thus parameterizing the interior space of the ellipsoid. By applying the node density modulation function and inputting the spatial coordinates of any point within the ellipsoid, the output is the theoretical node density at that point. Within the parameterized ellipsoidal space, the three-dimensional coordinates of each new node are calculated according to the density distribution calculated by the node density modulation function; the set of coordinates of these new nodes constitutes the next-generation candidate location point cloud.

8. The partial discharge detection and localization method based on fluorescent optical fiber according to claim 7, characterized in that, The process of applying the node density modulation function includes the following steps: Given the spatial coordinates of any point within the ellipsoid, first perform an affine transformation to map it to the unit sphere parameter space; The density modulation function is input to the unit sphere parameter space, and the density modulation function consists of three core components: Radial density decay component: Along the principal axis of the ellipsoid, the node density decreases exponentially to ensure that the sampling points near the edge are sparse; Local curvature sensitive component: Based on the difference in the semi-axis length of each axis of the ellipsoid, the density distribution is dynamically adjusted, and the sampling density is automatically enhanced in high curvature areas; Historical iteration correction component: Combined with the node distribution error of the previous iteration, feedback adjustment is applied to optimize the smoothness and continuity of the current density field. The obtained initial density values ​​are truncated by upper and lower bounds to fall within a preset reasonable range; the final output is the theoretical node density of the nodes in the current ellipsoidal space.

9. The partial discharge detection and localization method based on fluorescent optical fiber according to claim 1, characterized in that, It also includes the process where, when a local discharge occurs, photons are coupled into the fiber by the trapping field, forming an initial photon flow. The photon trapping field originates from the microstructural modification of the fluorescent fiber, where a nonlinear optical coating is prepared on the fiber surface to actively attract and confine photons.

10. A partial discharge detection and localization system based on fluorescent optical fiber, implementing the partial discharge detection and localization method based on fluorescent optical fiber as described in any one of claims 1-9, characterized in that, include: The photon trapping module is used to couple photons into the interior of the optical fiber by the trapping field when a local discharge occurs, forming an initial photon flow. The photon stream conversion module is used to process the initial photon stream propagating along the fluorescent fiber through a time stamp embedding process. The time stamp embedding utilizes the dispersion characteristics of the fiber and the interaction between photons and fluorescent materials to implant a unique time signature into the photon stream. The arrival time of photons is synchronously monitored at both ends of the fiber by photomultiplier tubes. Each photon stream is converted into time series data, which is a time stamp sequence containing the precise time difference information of the photons arriving at the sensors at both ends. The position mapping module is used to analyze the time difference of the time stamp sequence and calculate the location of partial discharge through the position mapping algorithm. Based on the constancy of photon propagation speed in optical fiber and the correlation of time stamp sequence, the time difference is first converted into a relative distance parameter. Then, the geometric layout of the matching optical fiber is iteratively optimized to finally generate the discharge position coordinates. The output is the three-dimensional spatial coordinates of the partial discharge point.

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