Broken line fault monitoring method of FTU (Feeder Terminal Unit) and related equipment

Abstract

The invention relates to an FTU (feeder terminal unit) broken line fault monitoring method, which comprises the following steps of: performing electrical data acquisition on an FTU line through a preset electrical mutual inductor to obtain electrical data; wherein the electrical data comprises voltage data and current data; performing phase angle calculation on the voltage data and the current data to obtain a phase angle difference value; if the phase angle difference value is not in the standard range, calling a database to obtain the attribute of the FTU line; through a preset distributed parameter model, based on the attribute of the line, the phase angle and the electrical data, carrying out broken line positioning on the line to obtain a broken line area; performing dynamic feature identification on the electrical parameters corresponding to the broken line area to obtain fault dynamic features, and performing fault type analysis on the broken line area based on the fault dynamic features to obtain a fault type monitoring report; the technical problems that a traditional fault monitoring method depends on manual inspection and a simple fault indicator, and it is difficult to meet the positioning precision and judge the fault type are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of fault monitoring, and in particular to a method for monitoring a disconnection fault of a FTU and related equipment. Background Art

[0002] With the expansion of power system scale and the increase of complexity, timely and accurate monitoring of line faults has become increasingly important. Traditional fault monitoring methods rely on manual inspections and simple fault indicators. These methods have limitations in fault response speed, positioning accuracy and fault type judgment, and are difficult to meet the requirements of modern power systems for high efficiency and high reliability. In particular, line break faults, due to their strong suddenness and wide impact range, once they occur, may cause large-scale power outages, seriously affecting the safe and stable operation of the power system. Therefore, it is particularly urgent to develop a method that can automatically, quickly and accurately monitor and locate line break faults. Summary of the invention

[0003] The main purpose of the present invention is to provide a FTU disconnection fault monitoring method and related equipment, which solves the technical problem that the traditional fault monitoring method relies on manual inspection and simple fault indicators, and is difficult to meet the positioning accuracy and judge the fault type.

[0004] To achieve the above object, the present invention provides a method for monitoring a line disconnection fault of a FTU, comprising the following steps: The electrical data of the FTU circuit is collected through the preset electrical transformer to obtain electrical data; wherein the electrical data includes voltage data and current data; Performing phase angle calculation on the voltage data and the current data to obtain a phase angle difference; Determine whether the phase angle difference is within the standard range, and if the phase angle difference is not within the standard range, call the database to obtain the attributes of the FTU line; By using a preset distributed parameter model, based on the attributes of the line, the phase angle and the electrical data, the line is disconnected and a disconnection area is obtained; Dynamic feature recognition is performed on electrical parameters corresponding to the disconnection area to obtain dynamic features of the fault, and a fault type analysis is performed on the disconnection area based on the dynamic features of the fault to obtain a fault type monitoring report.

[0005] Furthermore, electrical data of the FTU circuit is collected through a preset electrical transformer to obtain electrical data, including: The electrical signal of the FTU line is collected through the preset electrical transformer to obtain the electrical analog signal; Convert the electrical analog signal into a digital signal by a preset ADC converter to obtain a digital conversion signal; amplifying the digital conversion signal to obtain a digital amplified signal; A voltage signal and a current signal in the digital amplified signal are extracted to obtain an electrical signal, and the electrical signal is used as electrical data.

[0006] Further, performing phase angle calculation on the voltage data and the current data to obtain a phase angle difference includes: Using a preset clock system to perform time synchronization on the voltage data and the current data respectively, to obtain corresponding voltage time synchronization data and current time synchronization data; Convert the voltage timing synchronization data and the current timing synchronization data into complex form to obtain corresponding voltage complex form data and current complex form data; wherein the complex form includes a real part and an imaginary part, the real part represents the instantaneous amplitude of the electrical signal, and the imaginary part reflects the phase information of the electrical signal; Performing phase angle calculation on the voltage complex form data to obtain a voltage phase angle; Performing phase angle calculation on the current complex form data to obtain the current phase angle; The phase angle difference is calculated for the voltage phase angle and the current phase angle point by point to obtain the phase angle difference.

[0007] Furthermore, the line is located for disconnection based on the attributes of the line, the phase angle and the electrical data through a preset distributed parameter model to obtain a disconnection area, including: Inputting the line attributes, the phase angle and the electrical data into a preset distributed parameter model to identify the fault location, and obtaining a potential fault identification location; Extracting fault signals from the potential fault identification position to obtain fault characteristic signals; wherein the fault characteristic signals include impedance change characteristic signals and reflection waveform characteristic signals; Performing waveform calculation on the impedance change characteristic signal to obtain abnormal waveform parameters; wherein the abnormal waveform parameters include peak distortion coefficient, zero-crossing drift, and increased harmonic content; Performing spectrum calculation on the reflected waveform characteristic signal to obtain spectrum distortion index; wherein the spectrum distortion index includes harmonic phase angle, spectrum flatness, and interharmonic distortion rate; By using a preset traveling wave algorithm, the line is located for disconnection based on the abnormal waveform parameters and the spectrum distortion index to obtain a disconnection area.

[0008] Furthermore, the line is located for disconnection based on the abnormal waveform parameters and the spectrum distortion index by using a preset traveling wave algorithm to obtain a disconnection area, including: Extract key parameters of the abnormal waveform parameters to obtain abnormal key parameters; wherein the abnormal key parameters include the fault occurrence time, wavefront steepness, and waveform zero-crossing time; Perform frequency domain identification on the spectrum distortion index to obtain a sudden change in harmonic frequency and frequency response; wherein the sudden change in frequency response includes a change in harmonic frequency and a shift in fundamental frequency; Obtaining a time difference between at least two preset sensors when receiving a fault traveling wave, and obtaining a distance from the fault point to each of the sensors based on the time difference and the speed of the fault traveling wave; Within the distance from the fault point to each of the sensors, the abnormal key parameters and the sudden changes of harmonic frequency and frequency response are located by a preset traveling wave algorithm to obtain the disconnection area.

[0009] Furthermore, dynamic feature recognition is performed on the electrical parameters corresponding to the disconnection area to obtain dynamic features of the fault, including: Extracting the fault signal corresponding to the disconnection area to obtain a fault extraction feature signal; Performing spectrum content analysis on the fault extraction feature signal by using fast Fourier transform to obtain a spectrum feature set; wherein the spectrum feature set includes harmonics, subharmonic components and amplitude changes of the frequency; Performing signal spectrum calculation on the spectrum feature set to obtain an entropy value of a fault feature signal and an energy distribution of the fault feature signal; Drawing a frequency drift trajectory of the fault characteristic signal based on the entropy value of the fault characteristic signal and the energy distribution of the fault characteristic signal; The fault characteristic signal is captured and identified based on the frequency drift trajectory, and the fault dynamic characteristics of the fault characteristic signal evolving over time are obtained.

[0010] Furthermore, based on the dynamic characteristics of the fault, the fault type analysis is performed on the disconnection area to obtain a fault type monitoring report, including: Constructing a fault dynamic matrix based on the fault dynamic characteristics; Performing projection dimension reduction on the fault dynamic matrix to obtain a projection matrix; The projection matrix is ​​input into a preset fault type analysis algorithm for a decomposition to obtain a classification matrix and a probability matrix mapped by the classification matrix; wherein the elements of the classification matrix represent classification labels, and the elements of the probability matrix represent probability values ​​corresponding to the classification labels; Determine whether the probability values ​​corresponding to the elements of the probability matrix are within the preset probability values. If not, delete the classification matrix elements that are not within the preset probability values ​​to obtain a deletion matrix. Inputting the deletion matrix into a preset fault type analysis algorithm for secondary decomposition until the probability values ​​corresponding to the elements of the deletion matrix are within the preset probability values; If the probability value corresponding to the element of the deleted matrix is ​​within the preset probability value, the standard classification matrix is ​​obtained; Based on the standard classification matrix, a fault type analysis is performed on the disconnection area to obtain a fault type monitoring report.

[0011] The present invention also provides a FTU disconnection fault monitoring device, comprising: The acquisition module is used to acquire electrical data of the FTU circuit through a preset electrical transformer to obtain electrical data; wherein the electrical data includes voltage data and current data; A calculation module, used for performing phase angle calculation on the voltage data and the current data to obtain a phase angle difference; A calling module is used to determine whether the phase angle difference is within the standard range. If the phase angle difference is not within the standard range, a database is called to obtain the attributes of the line of the FTU; A positioning module, used to locate the line disconnection based on the attributes of the line, the phase angle and the electrical data through a preset distributed parameter model to obtain a disconnection area; The analysis module is used to perform dynamic feature recognition on the electrical parameters corresponding to the disconnection area to obtain dynamic features of the fault, perform fault type analysis on the disconnection area based on the dynamic features of the fault, and obtain a fault type monitoring report.

[0012] The present invention also provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of any one of the above methods when executing the computer program.

[0013] The present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of any of the above-mentioned methods are implemented.

[0014] The FTU line break fault monitoring method provided by the present invention comprises the following steps: collecting electrical data of the FTU line through a preset electrical mutual inductor to obtain electrical data; wherein the electrical data includes voltage data and current data; performing phase angle calculation on the voltage data and the current data to obtain a phase angle difference; judging whether the phase angle difference is within a standard range, if the phase angle difference is not within the standard range, calling a database to obtain the attributes of the FTU line; locating the line break based on the attributes of the line, the phase angle and the electrical data through a preset distributed parameter model to obtain a line break area; performing dynamic feature recognition on the electrical parameters corresponding to the line break area to obtain a fault dynamic feature, performing a fault type analysis on the line break area based on the fault dynamic feature to obtain a fault type monitoring report; through the above technical solution, the technical problem that the traditional fault monitoring method relies on manual inspection and simple fault indicators and is difficult to meet the positioning accuracy and judge the fault type is solved, and fast and accurate fault monitoring and positioning are achieved, which is helpful to isolate the fault in time, prevent the fault from spreading, and ensure the beneficial effects of stable operation of the power system and continuity of power supply to users. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a schematic diagram of the steps of a method for monitoring a line break fault of an FTU in one embodiment of the present invention; Figure 2 is a structural block diagram of a line break fault monitoring device of an FTU in one embodiment of the present invention; Figure 3 It is a schematic block diagram of the structure of a computer device according to an embodiment of the present invention.

[0016] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0018] like Figure 1 As shown, Figure 1 It is a schematic diagram of the steps of a method for monitoring a line break fault of an FTU in one embodiment of the present invention; In one embodiment of the present invention, a method for monitoring a line disconnection fault of a FTU is provided, comprising the following steps: Step S1, collecting electrical data of the FTU line through a preset electrical transformer to obtain electrical data; wherein the electrical data includes voltage data and current data.

[0019] Specifically, in this step, the electrical data collection of the FTU line through the pre-set electrical transformer is the basic link to realize the fault monitoring and management of the power system. Specifically, this process involves the following points: Electrical transformer: This is a common sensor device in the power system, which is pre-installed (i.e. "pre-set") at the key nodes of the power line monitored by the feeder terminal unit (FTU). Their function is to sense and convert current and voltage signals to make them suitable for further measurement and analysis. The current transformer is mainly responsible for detecting the current flow in the line, while the voltage transformer is used to measure the voltage level of the line. FTU line: FTU, i.e. feeder terminal unit, is an intelligent device installed on the feeder of the power distribution network, responsible for monitoring the line status and performing protection and control functions. Here, "FTU line" refers to the part of the power transmission network directly monitored by the FTU, including all cables or overhead lines from the substation outlet to the user access point. Electrical data collection: refers to the use of electrical transformers to continuously collect real-time electrical parameter activities on the power line. These data mainly include voltage data and current data. The voltage data reflects the magnitude of the potential difference between the two ends of the line, while the current data indicates the intensity of the charge flow through the line. These two data are the basic basis for evaluating the operating status of the line and identifying abnormal conditions. Obtaining electrical data: Through transformer conversion and signal conditioning, the original physical quantities (current and voltage) are converted into easy-to-process electrical signals or digital signals, which are then recorded by the data acquisition system. These collected electrical data, that is, the real-time measurement values ​​of voltage and current, are the basis for subsequent fault detection, phase angle calculation, and various analyses. They are essential for determining whether the line is in normal working condition and for rapid response when a fault occurs. In summary, this step realizes real-time monitoring of key electrical parameters of power lines through physical equipment (electrical transformers) and electronic technology, providing necessary data support for fault warning, positioning, and maintenance of power systems.

[0020] Step S2, performing phase angle calculation on the voltage data and the current data to obtain a phase angle difference.

[0021] Specifically, in the monitoring of the power system, it is a crucial analysis step to calculate the phase angle of the voltage data and the current data to obtain the phase angle difference, as follows: The voltage data and the current data are real-time measurement values ​​collected from the line monitored by the FTU through the electrical transformer in the previous step. The phase angle is a basic feature of alternating current, representing the instantaneous position of the voltage or current waveform relative to a reference point (usually a zero-phase reference point). In a three-phase system, the phase angle also involves the relative position between the phases. Phase angle calculation: This process involves converting the waveform data of the voltage and current into a complex form, usually by converting the time domain signal into the frequency domain through signal processing techniques such as fast Fourier transform (FFT), so that the phase angle of the voltage and current can be directly read. Specifically for each pair of voltage-current data, the phase angle difference can be obtained by comparing their phase relationship. Phase angle difference: Under normal operating conditions of the power system, the load is usually purely resistive, at which time the current and voltage are in phase, and the phase angle difference is close to zero. However, when a line fault such as a broken line, short circuit, or grounding occurs, the impedance characteristics of the line will change, causing the phase relationship between voltage and current to change, that is, the phase angle difference is no longer zero or the standard value. Therefore, by calculating and analyzing these phase angle differences, the operating status of the line and potential fault information can be reflected. In summary, by calculating the phase angle of voltage data and current data, and further obtaining the phase angle difference, it can be used as an effective means of fault warning and preliminary diagnosis, because it can sensitively reflect the abnormal changes in electrical parameters in the power system, providing important clues for subsequent fault location and processing.

[0022] Step S3, determining whether the phase angle difference is within a standard range; if the phase angle difference is not within a standard range, calling a database to obtain the attributes of the FTU line.

[0023] Specifically, in monitoring the power system, judging whether the phase angle difference is within the standard range is a key step in evaluating whether the line operation status is normal. The phase angle difference refers to the difference between the phases of the voltage and current signals obtained by analyzing them. Under normal operating conditions, the phase angle difference is usually maintained within a preset standard range, which reflects the expected state of system design and operation. When the phase angle difference is not within the standard range, it usually indicates that there may be abnormal conditions in the line, such as line break, short circuit or load mutation, because these faults or abnormalities will affect the impedance characteristics of the line, thereby causing changes in the relationship between the voltage and current phases. At this point, the system will automatically trigger the next action - calling the database to obtain the attributes of the FTU line. Calling the database to obtain the attributes of the FTU line means that the system uses the pre-entered database information to query the detailed information of the line associated with the FTU. These attributes include but are not limited to the length, material, cross-sectional area, geographical location, historical fault records, etc. of the line. This information is crucial for subsequent fault location and processing. By combining the real-time monitored phase angle difference abnormal information with the specific properties of the line, the cause of the fault can be analyzed more accurately, guiding fault detection and emergency repair work, and ensuring the stable operation and rapid recovery of the power system.

[0024] Step S4, using a preset distributed parameter model, based on the attributes of the line, the phase angle and the electrical data, the line is disconnected and a disconnection area is obtained.

[0025] Specifically, in the field of power system fault diagnosis, it is an advanced analysis method to locate the line break through the preset distributed parameter model. Specifically, the operation process of this step can be understood as follows: Distributed parameter model: This is a mathematical model used to describe and analyze the behavior of continuous distributed systems such as power lines. Compared with the concentrated parameter model, it takes into account the spatial distribution characteristics of system parameters (such as resistance, inductance, and capacitance), and is more suitable for dealing with transient phenomena on long-distance transmission lines, such as traveling wave propagation and reflection. The model presets the physical laws and mathematical relationships of the line, and can simulate and calculate the response of the line under different working conditions. Based on the attributes of the line: The "attributes" here refer to information related to the physical structure and electrical characteristics of the line, including but not limited to line length, conductor type, cross-sectional area, material, geographical environment, etc. These attributes directly affect the impedance characteristics and signal propagation characteristics of the line, and are indispensable input parameters in the model. The phase angle and electrical data: Using the phase angle difference calculated in the previous step, as well as the voltage and current electrical data collected in real time, these information are a direct reflection of the fault characteristics. Abnormal changes in the phase angle indicate changes in system impedance, while electrical data provide specific values ​​for energy flow and voltage-current relationships. The combination of the two is the key basis for locating line breaks. Locate line breaks: Input the above information into a distributed parameter model, which simulates the propagation and reflection process of traveling waves in the line when a fault occurs. By calculating the time difference (TOA) of the traveling wave arriving at different monitoring points or analyzing the characteristics of the traveling wave, combined with line properties and electrical parameters, the model can trace back and locate the area where the fault occurs, that is, determine the line break area. In summary, this step integrates physical models, real-time monitoring data, and basic line information, and uses advanced computing technology to achieve accurate positioning of power line break faults, providing a scientific basis for rapid response and repair of faults.

[0026] Step S5, performing dynamic feature recognition on the electrical parameters corresponding to the disconnection area to obtain dynamic features of the fault, performing fault type analysis on the disconnection area based on the dynamic features of the fault, and obtaining a fault type monitoring report.

[0027] Specifically, in the power system fault diagnosis process, dynamic feature recognition of the electrical parameters corresponding to the disconnection area is a key step to gain an in-depth understanding of the fault characteristics and progress. Specifically, this process includes: dynamic feature recognition: First, for the disconnection area that has been located, the system will intensively collect the electrical parameters of the area, such as instantaneous voltage and current changes, and the trend of these parameters over time. These data reflect the dynamic changes in the line state after the disconnection, including but not limited to current mutations, voltage drops, frequency fluctuations, etc. Through advanced signal processing techniques such as wavelet analysis and empirical mode decomposition (EMD), features reflecting the dynamic behavior of the fault are extracted from continuous electrical parameters, such as changes in specific frequency components, degree of waveform distortion, oscillation mode, etc. These are the dynamic features of the fault. Fault type analysis: Next, based on the extracted fault dynamic features, the type of disconnection fault is analyzed in depth using machine learning algorithms or expert systems. This analysis process involves the construction of feature vectors, pattern recognition, and the application of classification algorithms. For example, by comparing the features with a database of known fault modes, it is possible to identify whether the fault is a single-phase line break, a two-phase line break, or a multi-phase line break, or whether it is accompanied by other complex conditions, such as a ground fault. The algorithm improves the accuracy and speed of identification by learning the characteristic manifestations of similar faults in history. Fault type monitoring report generation: Finally, the above analysis results are summarized and organized into a fault type monitoring report. This report will not only clearly indicate the specific type of line break fault, but also contain dynamic feature analysis details to support the judgment, such as the numerical value of the feature parameter, waveform chart, spectrum analysis results, etc. The report may also evaluate the severity of the fault, the scope of impact, and the potential risks, providing a scientific basis for subsequent emergency repair decisions and system recovery. Through this series of analysis processes, power system maintenance personnel can quickly grasp the overall situation of the line break fault, take targeted countermeasures, and ensure the safety and stability of power supply.

[0028] In a specific embodiment, electrical data of the FTU circuit is collected by a preset electrical transformer to obtain electrical data, including: The electrical signal of the FTU line is collected through the preset electrical transformer to obtain the electrical analog signal; Convert the electrical analog signal into a digital signal by a preset ADC converter to obtain a digital conversion signal; amplifying the digital conversion signal to obtain a digital amplified signal; A voltage signal and a current signal in the digital amplified signal are extracted to obtain an electrical signal, and the electrical signal is used as electrical data.

[0029] Specifically, in the automated monitoring and protection mechanism of the power system, real-time electrical status monitoring of the distribution network lines is a very critical link. The scheme mentioned here details how to obtain and process electrical data from physical lines through a series of equipment and steps. The specific steps are as follows: Electrical signal acquisition: First, the lines responsible for the feeder terminal unit (FTU) are monitored using a preset electrical transformer. An electrical transformer is a sensor that can safely sense electrical signals in high-voltage or high-current lines and convert them into measurable low-voltage or low-current analog signals without directly interfering with the operation of the main circuit. This process ensures the safety of the operator and can effectively collect information about the actual working status of the line. Analog signal to digital signal conversion: Next, the collected electrical analog signal needs to be digitized for computer processing and remote transmission. This step is completed by a **preset ADC (analog-to-digital converter). The ADC device can convert continuously changing analog signals into discrete digital signals. This conversion process is achieved by sampling and quantizing analog signals so that the signals can be stored and analyzed in digital form. Digital signal amplification: The converted digital signals often need further processing to enhance their readability and analysis accuracy. The digital amplification step is to perform gain processing on these signals to increase the amplitude of the signals and ensure that even weak signal details can be clearly identified and analyzed, which is crucial for accurately detecting line conditions. Signal extraction and electrical data formation: Finally, the amplified digital signals contain the voltage and current information of the line. Through software or hardware filtering and signal processing technology, voltage and current signals are extracted from these composite signals. These signals are the core indicators for evaluating the health of the line, power flow and potential faults. The extracted voltage and current information are integrated together to form complete electrical data. These data can then be used for a variety of applications such as real-time monitoring, fault diagnosis, load forecasting, etc., to help power companies efficiently manage distribution networks. In summary, through a series of precise operations, this solution realizes the effective conversion from physical lines to analyzable data, providing a solid data foundation for the intelligent management of power systems.

[0030] In a specific embodiment, performing phase angle calculation on the voltage data and the current data to obtain a phase angle difference includes: Using a preset clock system to perform time synchronization on the voltage data and the current data respectively, to obtain corresponding voltage time synchronization data and current time synchronization data; Convert the voltage timing synchronization data and the current timing synchronization data into complex form to obtain corresponding voltage complex form data and current complex form data; wherein the complex form includes a real part and an imaginary part, the real part represents the instantaneous amplitude of the electrical signal, and the imaginary part reflects the phase information of the electrical signal; Performing phase angle calculation on the voltage complex form data to obtain a voltage phase angle; Performing phase angle calculation on the current complex form data to obtain the current phase angle; The phase angle difference is calculated for the voltage phase angle and the current phase angle point by point to obtain the phase angle difference.

[0031] Specifically, in power system fault monitoring, accurately calculating the phase angle difference between voltage and current is one of the key steps to identify abnormal system conditions. The following is a detailed explanation based on the steps provided: Timing synchronization: In order to ensure the consistency of voltage data and current data on the time axis, a preset clock system is used to accurately synchronize the two. This means that no matter when the voltage and current signals are collected, their corresponding time points can be ensured to be completely aligned, which is the basis for subsequent phase analysis. Through timing synchronization, voltage timing synchronization data and current timing synchronization data are obtained, ensuring the accuracy of the analysis. Complex form conversion: The synchronized time series data is further converted into complex form, which is a common and powerful means in signal processing. The complex representation can contain both the amplitude and phase information of the signal, where the real part represents the instantaneous amplitude of the signal (i.e., the strength of the signal), and the imaginary part reflects the phase information of the signal (i.e., the position of the signal on the time axis). This conversion provides a convenient mathematical basis for subsequent phase calculations, and voltage complex form data and current complex form data are obtained respectively. Phase angle calculation: Next, the converted voltage and current complex form data are respectively calculated for the phase angle. The phase angle is the angle between the signal waveform and the reference point (usually the positive zero crossing point), which directly reflects the phase state of the signal. Through mathematical operations, the voltage phase angle and current phase angle are extracted from the complex phase angle, and these angles are usually in degrees or radians. Phase angle difference calculation: Finally, the voltage phase angle and current phase angle at each corresponding time point are calculated point by point to obtain the phase difference between them. This phase difference value is an important indicator for analyzing the operating status of the power system, especially when identifying the type of fault (such as line break, short circuit, etc.). Abnormal phase angle difference often indicates the existence of faults or nonlinear loads in the system, providing direct clues for fault diagnosis. In summary, through strict timing synchronization, complex form conversion and analysis, the final phase angle difference becomes valuable information for evaluating the operating status of power lines and identifying fault areas, providing a scientific basis for fault monitoring and maintenance of power systems.

[0032] In a specific embodiment, a line disconnection location is performed on the line based on the attributes of the line, the phase angle and the electrical data through a preset distributed parameter model to obtain a disconnection area, including: Inputting the line attributes, the phase angle and the electrical data into a preset distributed parameter model to identify the fault location, and obtaining a potential fault identification location; Extracting fault signals from the potential fault identification position to obtain fault characteristic signals; wherein the fault characteristic signals include impedance change characteristic signals and reflection waveform characteristic signals; Performing waveform calculation on the impedance change characteristic signal to obtain abnormal waveform parameters; wherein the abnormal waveform parameters include peak distortion coefficient, zero-crossing drift, and increased harmonic content; Performing spectrum calculation on the reflected waveform characteristic signal to obtain spectrum distortion index; wherein the spectrum distortion index includes harmonic phase angle, spectrum flatness, and interharmonic distortion rate; By using a preset traveling wave algorithm, the line is located for disconnection based on the abnormal waveform parameters and the spectrum distortion index to obtain a disconnection area.

[0033] Specifically, in the power system fault diagnosis, the above-mentioned line break fault location scheme adopts distributed parameter model and advanced signal processing technology. The specific steps are as follows: Model input and potential fault identification: First, the known line attributes (such as line length, material, cross-sectional area, etc.), phase angle information (reflecting the phase relationship between current and voltage) and real-time electrical data (including voltage and current signals) are integrated and input into a preset distributed parameter model. The distributed parameter model can comprehensively analyze the line based on physical laws and line characteristics through complex mathematical calculations and simulations, and preliminarily identify the potential fault identification location, that is, those suspicious areas where the line may be broken. Fault characteristic signal extraction: For these potential fault locations, fault signal extraction is performed to separate the signal part directly related to the fault. These signals are subdivided into impedance change characteristic signals and reflection waveform characteristic signals. The impedance change reflects the abnormality of the line impedance, while the reflection waveform is a unique signal pattern caused by the reflection of the traveling wave at the breakpoint. The two together constitute the fault characteristic signal. Abnormal waveform parameter analysis: In-depth waveform calculation is performed on the impedance change characteristic signal to quantify the degree of abnormality and extract abnormal waveform parameters such as peak distortion coefficient (the degree of deformation at the top of the waveform), zero-crossing drift (the offset of the waveform zero-crossing position) and increased harmonic content (increase in non-fundamental components). These parameters reveal the changes in electrical parameters caused by the disconnection. Spectral distortion index calculation: The spectrum of the reflected waveform characteristic signal is calculated to analyze its performance in the frequency domain to obtain spectrum distortion indicators, including harmonic phase angle (phase offset of harmonic relative to the fundamental wave), spectrum flatness (uniformity of spectrum energy distribution) and interharmonic distortion rate (component content of non-integer multiples of the fundamental frequency). These indicators help identify specific fault characteristics. Travel wave algorithm locates the disconnection area: Finally, the preset traveling wave algorithm is used, combined with the abnormal waveform parameters and spectrum distortion indicators obtained previously, to accurately locate the disconnection area by calculating the propagation and reflection characteristics of the traveling wave at the fault point. The algorithm includes comparing the fault characteristic signal with the waveform predicted by the model, and using the time difference information to narrow the positioning range, and finally determine the exact location of the disconnection. The entire process integrates physical model simulation, signal processing technology and algorithm analysis, achieving efficient and accurate positioning of power line break faults, and providing strong technical support for rapid fault repair.

[0034] In a specific embodiment, a preset traveling wave algorithm is used to locate the line disconnection based on the abnormal waveform parameters and the spectrum distortion index to obtain the disconnection area, including: Extract key parameters of the abnormal waveform parameters to obtain abnormal key parameters; wherein the abnormal key parameters include the fault occurrence time, wavefront steepness, and waveform zero-crossing time; Perform frequency domain identification on the spectrum distortion index to obtain a sudden change in harmonic frequency and frequency response; wherein the sudden change in frequency response includes a change in harmonic frequency and a shift in fundamental frequency; Obtaining a time difference between at least two preset sensors when receiving a fault traveling wave, and obtaining a distance from the fault point to each of the sensors based on the time difference and the speed of the fault traveling wave; Within the distance from the fault point to each of the sensors, the abnormal key parameters and the sudden changes of harmonic frequency and frequency response are located by a preset traveling wave algorithm to obtain the disconnection area.

[0035] Specifically, the line break location scheme adopts a comprehensive analysis method to accurately locate the line break area in the power line through multiple steps, as follows: Key parameter extraction: First, the most critical indicators are extracted from the abnormal waveform parameters, including the moment of fault occurrence, that is, the time point when the fault first occurs; the wavefront steepness, which reflects the sharp change in the slope of the waveform front, which is related to the intensity of energy release when the fault occurs; and the waveform zero-crossing time, which identifies the waveform changes caused by the fault by analyzing the deviation of the waveform zero-crossing point. These key parameters provide a direct basis for fault identification and location. Frequency domain identification and harmonic analysis: Then, the spectrum distortion indicators are deeply analyzed to identify the changes in harmonic frequencies, that is, how the frequency components other than the fundamental wave are abnormal due to the fault; at the same time, the sudden changes in the frequency response are observed, including the increase and decrease of harmonic frequencies and the shift of the fundamental frequency. These sudden changes reveal the impact of the fault on the frequency characteristics of the system and further indicate the fault characteristics. Time difference calculation and distance estimation: Using at least two sensors arranged at different locations, measure the time difference (TOA) of each of them receiving the fault traveling wave, and combine it with the known traveling wave propagation speed (approximately equal to the speed of light). By simply multiplying the time difference by the speed formula, the approximate distance from each sensor to the fault point can be estimated. Comprehensive positioning of the broken wire area: Finally, combined with the key parameters extracted from the abnormal waveform parameters (fault occurrence time, wavefront steepness, waveform zero crossing time) and the frequency domain analysis results (changes in harmonic frequency and sudden changes in frequency response), as well as the distance information from each sensor to the fault point, a comprehensive analysis is performed using the preset traveling wave algorithm. This algorithm involves a complex mathematical model that can process the above-mentioned multi-source information. Through optimization algorithms or iterative processes, one or more most likely broken wire areas are finally determined within the distance range from the fault point to each sensor. This step improves the accuracy and reliability of positioning by integrating the characteristics of the time and frequency domains, providing accurate fault location information for rapid response and maintenance.

[0036] In a specific embodiment, dynamic feature recognition is performed on the electrical parameters corresponding to the disconnection area to obtain the dynamic features of the fault, including: Extracting the fault signal corresponding to the disconnection area to obtain a fault extraction feature signal; Performing spectrum content analysis on the fault extraction feature signal by using fast Fourier transform to obtain a spectrum feature set; wherein the spectrum feature set includes harmonics, subharmonic components and amplitude changes of the frequency; Performing signal spectrum calculation on the spectrum feature set to obtain an entropy value of a fault feature signal and an energy distribution of the fault feature signal; Drawing a frequency drift trajectory of the fault characteristic signal based on the entropy value of the fault characteristic signal and the energy distribution of the fault characteristic signal; The fault characteristic signal is captured and identified based on the frequency drift trajectory, and the fault dynamic characteristics of the fault characteristic signal evolving over time are obtained.

[0037] Specifically, this step is to conduct an in-depth electrical parameter analysis of the located broken line area to identify the dynamic characteristics of the fault, which is explained as follows: Fault signal extraction: First, the signal part directly related to the fault is extracted from the monitoring data of the broken line area. This process is called fault feature signal extraction. This is done to separate the clear fault signal from the complex background noise of the power grid and provide a pure input for subsequent analysis. Spectral content analysis: Using the fast Fourier transform (FFT), the extracted fault feature signal is converted from the time domain to the frequency domain to obtain a spectrum feature set. This conversion reveals the different frequency components contained in the signal, with special attention to the harmonics (integer multiples of the fundamental frequency), subharmonic components (non-integer multiples of the frequency) and their corresponding amplitude changes. This information is crucial to understanding the nature of the fault. Signal spectrum calculation: Further, the spectrum feature set is deeply analyzed to calculate the entropy value and energy distribution of the fault feature signal. The entropy value measures the complexity or uncertainty of the signal spectrum, and the energy distribution reflects the contribution of different frequency components. The two together depict the spectral feature profile of the fault signal. Frequency drift trajectory drawing: Based on the entropy value and energy distribution calculated above, the frequency drift trajectory of the fault characteristic signal is displayed graphically. This trajectory can help to intuitively understand the changing trend of the fault over time, that is, the dynamic behavior of the fault signal in the frequency domain, including frequency offset or fluctuation. Fault dynamic feature identification: Finally, by analyzing the frequency drift trajectory, the dynamic characteristics of the fault characteristic signal evolving over time are captured and identified. This means identifying the specific mode of fault development, the changing law of frequency characteristics, etc., which is extremely important for diagnosing the fault type, assessing the severity of the fault, and predicting the development trend of the fault. The entire process improves the accuracy and timeliness of fault diagnosis by tracking and analyzing these dynamic characteristics.

[0038] In a specific embodiment, a fault type analysis is performed on the disconnection area based on the fault dynamic characteristics to obtain a fault type monitoring report, including: Constructing a fault dynamic matrix based on the fault dynamic characteristics; Performing projection dimension reduction on the fault dynamic matrix to obtain a projection matrix; The projection matrix is ​​input into a preset fault type analysis algorithm for a decomposition to obtain a classification matrix and a probability matrix mapped by the classification matrix; wherein the elements of the classification matrix represent classification labels, and the elements of the probability matrix represent probability values ​​corresponding to the classification labels; Determine whether the probability values ​​corresponding to the elements of the probability matrix are within the preset probability values. If not, delete the classification matrix elements that are not within the preset probability values ​​to obtain a deletion matrix. Inputting the deletion matrix into a preset fault type analysis algorithm for secondary decomposition until the probability values ​​corresponding to the elements of the deletion matrix are within the preset probability values; If the probability value corresponding to the element of the deleted matrix is ​​within the preset probability value, the standard classification matrix is ​​obtained; Based on the standard classification matrix, a fault type analysis is performed on the disconnection area to obtain a fault type monitoring report.

[0039] Specifically, this step is to conduct in-depth data processing and analysis of the acquired fault dynamic features to accurately identify the fault type of the disconnection area and form a detailed monitoring report. The specific process is as follows: Construction of fault dynamic matrix: First, the extracted fault dynamic features are organized into a mathematical expression, namely the fault dynamic matrix. This matrix integrates all information about the change of faults over time and provides a structured data basis for subsequent fault type analysis. Projection dimension reduction: Since the original fault dynamic matrix may contain a large number of feature dimensions, in order to improve analysis efficiency and reduce computational complexity, it is converted into a more compact projection matrix through projection dimension reduction technology. This step aims to retain the most critical information while removing redundant dimensions. One-time decomposition and classification matrix generation: Next, the obtained projection matrix is ​​input into the preset fault type analysis algorithm for the first decomposition process. This process produces two outputs: a classification matrix and a probability matrix. Each element in the classification matrix represents a label of a fault type, while the element at the corresponding position of the probability matrix represents the confidence or probability value of the fault type being identified. Probability value screening: Check the probability matrix. If the probability value of some classifications is lower than the preset threshold (i.e., not within the preset probability value), the corresponding low-probability elements in the classification matrix will be deleted to generate a deletion matrix. This operation helps to eliminate unclear or low-credibility classification results. Secondary decomposition until the conditions are met: Repeat the processing of the fault type analysis algorithm and further decompose the deletion matrix until the probability values ​​of all remaining classifications meet or exceed the preset probability value standards. This iterative process ensures the accuracy and reliability of the final classification. Obtain the standard classification matrix: When all the remaining classification probability values ​​meet the preset conditions, the obtained matrix is ​​regarded as the standard classification matrix. This shows that each of the classifications has sufficient credibility and can be used as an effective basis for fault type analysis. Fault type analysis and report generation: Based on the standard classification matrix, the fault type of the disconnection area is finally confirmed, and a fault type monitoring report is compiled accordingly. This report summarizes the type, probability and basis of the fault analysis, providing a scientific basis for subsequent maintenance decisions.

[0040] The above describes the FTU disconnection fault monitoring method in the embodiment of the present invention. The following describes the FTU disconnection fault monitoring device in the embodiment of the present invention. Figure 2 In one embodiment of the present invention, a device for monitoring a line failure of a FTU includes: The acquisition module 21 is used to acquire electrical data of the FTU circuit through a preset electrical transformer to obtain electrical data; wherein the electrical data includes voltage data and current data; A calculation module 22, used for performing phase angle calculation on the voltage data and the current data to obtain a phase angle difference; A calling module 23 is used to determine whether the phase angle difference is within the standard range. If the phase angle difference is not within the standard range, a database is called to obtain the attributes of the line of the FTU; A positioning module 24 is used to locate the line disconnection based on the attributes of the line, the phase angle and the electrical data through a preset distributed parameter model to obtain a disconnection area; The analysis module 25 is used to perform dynamic feature recognition on the electrical parameters corresponding to the disconnection area to obtain dynamic features of the fault, and perform fault type analysis on the disconnection area based on the dynamic features of the fault to obtain a fault type monitoring report.

[0041] In this embodiment, for the specific implementation of each unit in the above system embodiment, please refer to the above method embodiment, which will not be repeated here.

[0042] Reference Figure 3 The present invention also provides a computer device in an embodiment, wherein the internal structure of the computer device can be as follows: Figure 3 As shown. The computer device includes a processor, a memory, a display screen, an input device, a network interface and a database connected through a system bus. Among them, the processor designed by the computer is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the corresponding data in this embodiment. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the above method is implemented.

[0043] Those skilled in the art will understand that Figure 3 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied.

[0044] An embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the above method is implemented. It can be understood that the computer-readable storage medium in this embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0045] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided by the present invention and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double-speed data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM.

[0046] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0047] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for monitoring a line break fault of a FTU, characterized in that: The following steps are involved: The electrical data of the FTU circuit is collected through the preset electrical transformer to obtain electrical data; wherein the electrical data includes voltage data and current data; Performing phase angle calculation on the voltage data and the current data to obtain a phase angle difference; Determine whether the phase angle difference is within the standard range, and if the phase angle difference is not within the standard range, call the database to obtain the attributes of the FTU line; By using a preset distributed parameter model, based on the attributes of the line, the phase angle and the electrical data, the line is disconnected and a disconnection area is obtained; Dynamic feature recognition is performed on electrical parameters corresponding to the disconnection area to obtain dynamic features of the fault, and a fault type analysis is performed on the disconnection area based on the dynamic features of the fault to obtain a fault type monitoring report.

2. The FTU disconnection fault monitoring method according to claim 1, characterized in that: The electrical data of the FTU circuit is collected through the preset electrical transformer to obtain electrical data, including: The electrical signal of the FTU line is collected through the preset electrical transformer to obtain the electrical analog signal; Convert the electrical analog signal into a digital signal by a preset ADC converter to obtain a digital conversion signal; amplifying the digital conversion signal to obtain a digital amplified signal; A voltage signal and a current signal in the digital amplified signal are extracted to obtain an electrical signal, and the electrical signal is used as electrical data.

3. The FTU disconnection fault monitoring method according to claim 2, characterized in that: Performing phase angle calculation on the voltage data and the current data to obtain a phase angle difference includes: Using a preset clock system to perform time synchronization on the voltage data and the current data respectively, to obtain corresponding voltage time synchronization data and current time synchronization data; Convert the voltage timing synchronization data and the current timing synchronization data into complex form to obtain corresponding voltage complex form data and current complex form data; wherein the complex form includes a real part and an imaginary part, the real part represents the instantaneous amplitude of the electrical signal, and the imaginary part reflects the phase information of the electrical signal; Performing phase angle calculation on the voltage complex form data to obtain a voltage phase angle; Performing phase angle calculation on the current complex form data to obtain the current phase angle; The phase angle difference is calculated for the voltage phase angle and the current phase angle point by point to obtain the phase angle difference.

4. The FTU disconnection fault monitoring method according to claim 1, characterized in that: Through a preset distributed parameter model, based on the attributes of the line, the phase angle and the electrical data, the line is located to obtain a line break area, including: Inputting the line attributes, the phase angle and the electrical data into a preset distributed parameter model to identify the fault location, and obtaining a potential fault identification location; Extracting fault signals from the potential fault identification position to obtain fault characteristic signals; wherein the fault characteristic signals include impedance change characteristic signals and reflection waveform characteristic signals; Performing waveform calculation on the impedance change characteristic signal to obtain abnormal waveform parameters; wherein the abnormal waveform parameters include peak distortion coefficient, zero-crossing drift, and increased harmonic content; Performing spectrum calculation on the reflected waveform characteristic signal to obtain spectrum distortion index; wherein the spectrum distortion index includes harmonic phase angle, spectrum flatness, and interharmonic distortion rate; By using a preset traveling wave algorithm, the line is located for disconnection based on the abnormal waveform parameters and the spectrum distortion index to obtain a disconnection area.

5. The FTU disconnection fault monitoring method according to claim 4, characterized in that: By using a preset traveling wave algorithm, based on the abnormal waveform parameters and the spectrum distortion index, the line is located to obtain a disconnection area, including: Extract key parameters of the abnormal waveform parameters to obtain abnormal key parameters; wherein the abnormal key parameters include the fault occurrence time, wavefront steepness, and waveform zero-crossing time; Perform frequency domain identification on the spectrum distortion index to obtain a sudden change in harmonic frequency and frequency response; wherein the sudden change in frequency response includes a change in harmonic frequency and a shift in fundamental frequency; Obtaining a time difference between at least two preset sensors when receiving the fault traveling wave, and obtaining a distance from the fault point to each of the sensors based on the time difference and the speed of the fault traveling wave; Within the distance from the fault point to each of the sensors, the abnormal key parameters and the sudden changes of harmonic frequency and frequency response are located by a preset traveling wave algorithm to obtain the disconnection area.

6. The FTU disconnection fault monitoring method according to claim 1, characterized in that: Dynamic feature recognition is performed on the electrical parameters corresponding to the disconnection area to obtain dynamic features of the fault, including: Extracting the fault signal corresponding to the disconnection area to obtain a fault extraction feature signal; Performing spectrum content analysis on the fault extraction feature signal by using fast Fourier transform to obtain a spectrum feature set; wherein the spectrum feature set includes harmonics, subharmonic components and amplitude changes of the frequency; Performing signal spectrum calculation on the spectrum feature set to obtain an entropy value of a fault feature signal and an energy distribution of the fault feature signal; Drawing a frequency drift trajectory of the fault characteristic signal based on the entropy value of the fault characteristic signal and the energy distribution of the fault characteristic signal; The fault characteristic signal is captured and identified based on the frequency drift trajectory, and the fault dynamic characteristics of the fault characteristic signal evolving over time are obtained.

7. The FTU disconnection fault monitoring method according to claim 1, characterized in that: Based on the dynamic characteristics of the fault, the fault type analysis is performed on the disconnection area to obtain a fault type monitoring report, including: Constructing a fault dynamic matrix based on the fault dynamic characteristics; Performing projection dimension reduction on the fault dynamic matrix to obtain a projection matrix; The projection matrix is ​​input into a preset fault type analysis algorithm for a decomposition to obtain a classification matrix and a probability matrix mapped by the classification matrix; wherein the elements of the classification matrix represent classification labels, and the elements of the probability matrix represent probability values ​​corresponding to the classification labels; Determine whether the probability values ​​corresponding to the elements of the probability matrix are within the preset probability values. If not, delete the classification matrix elements that are not within the preset probability values ​​to obtain a deletion matrix. Inputting the deletion matrix into a preset fault type analysis algorithm for secondary decomposition until the probability values ​​corresponding to the elements of the deletion matrix are within the preset probability values; If the probability value corresponding to the element of the deleted matrix is ​​within the preset probability value, the standard classification matrix is ​​obtained; Based on the standard classification matrix, a fault type analysis is performed on the disconnection area to obtain a fault type monitoring report.

8. A FTU disconnection fault monitoring device, characterized in that: include: The acquisition module is used to acquire electrical data of the FTU circuit through a preset electrical transformer to obtain electrical data; wherein the electrical data includes voltage data and current data; A calculation module, used for performing phase angle calculation on the voltage data and the current data to obtain a phase angle difference; A calling module is used to determine whether the phase angle difference is within the standard range. If the phase angle difference is not within the standard range, a database is called to obtain the attributes of the line of the FTU; A positioning module, used to locate the line disconnection based on the attributes of the line, the phase angle and the electrical data through a preset distributed parameter model to obtain a disconnection area; The analysis module is used to perform dynamic feature recognition on the electrical parameters corresponding to the disconnection area to obtain dynamic features of the fault, perform fault type analysis on the disconnection area based on the dynamic features of the fault, and obtain a fault type monitoring report.

9. A computer device comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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