An insulator pollution flashover risk early warning method and system based on multi-parameter fusion

Abstract

This invention belongs to the field of insulation monitoring technology, specifically relating to a method and system for early warning of insulator pollution flashover risk based on multi-parameter fusion. The method includes: acquiring transient leakage current signals and environmental temperature and humidity data; calculating equivalent pulse discharge intensity characteristics; constructing a hydration conductivity factor that maps the synergistic effect of temperature and humidity; calculating an energy accumulation index based on the product basis of the equivalent pulse discharge intensity characteristics and the hydration conductivity factor, and its first derivative approximation term; dynamically generating an early warning threshold based on the statistical distribution characteristics of the energy accumulation index within a time window and the benchmark drift compensation; comparing the energy accumulation index with the early warning threshold to determine the pollution flashover risk and outputting an early warning signal. This invention can filter out natural fluctuations in microclimate and keenly capture discharge surge trends, achieving early warning of insulator pollution flashover risk.

Description

Technical Field

[0001] This invention relates to the field of insulation monitoring technology. More specifically, this invention relates to a method and system for early warning of insulator flashover risk based on multi-parameter fusion. Background Technology

[0002] As the core external insulation component of high-voltage transmission lines, insulators are exposed to the complex outdoor atmospheric environment for a long time. Their surfaces are extremely prone to the adhesion of industrial dust and natural salt spray. Under humid microclimate conditions, the adhering dirt layer becomes damp and dissolves to form a continuous conductive water film. With the distortion of the local electric field, early corona discharge and local micro-arcs will be generated on the surface. If not intervened in time, the arc will extend rapidly and eventually cause a highly destructive flashover power outage accident, threatening the safety of the power grid.

[0003] Existing monitoring technologies typically involve installing sensors and weather probes at the grounding end of insulators to collect the absolute effective value of steady-state leakage current and ambient temperature and humidity. The underlying operation and maintenance platform usually relies on manually preset experience limits for judgment. When the amplitude of steady-state leakage current exceeds a specific mark or the ambient relative humidity reaches a certain level, an alarm is triggered directly. Alternatively, a mechanical early warning linkage can be achieved by simply linearly weighting the steady-state current and temperature and humidity values ​​and calculating a static score.

[0004] However, the evolution of partial discharge in insulators is a complex process governed by multiple physical mechanisms. Under actual operating conditions, leakage pulse mutations are not only related to the thickness of contamination, but also affected by transient catalytic effects of microclimate fluctuations. Existing absolute thresholds and simple weighting methods have severed the physical catalytic relationship between meteorological conditions and water film expansion and conductive ion migration, and have ignored the transient pulse thermal effect characteristics hidden in environmental noise. This makes it impossible for the system to accurately measure the dynamic destructive potential energy of the evolution to the arcing state. When faced with rapid changes in microclimate, it is very easy to have serious early warning delays or frequent false alarms caused by natural environmental fluctuations. Summary of the Invention

[0005] To address the technical problems of existing technologies that sever the physical-catalytic relationship between meteorological and electrical parameters and ignore transient pulse characteristics, thus failing to accurately measure the dynamic destructive potential energy of insulation degradation and leading to delayed early warnings and frequent false alarms under microclimate fluctuations, this invention provides solutions in the following aspects.

[0006] In a first aspect, the present invention provides an insulator flashover risk early warning method based on multi-parameter fusion, comprising: The transient leakage current signal of the insulator and the ambient temperature and humidity data are acquired in multiple consecutive sampling periods; the instantaneous power of the transient leakage current signal is approximated by integration in the discrete time domain to obtain the equivalent pulse discharge intensity characteristics that characterize the partial discharge intensity in each sampling period. Based on environmental temperature and humidity data, a hydration conductivity factor that maps the synergistic catalytic effect of temperature and humidity was constructed. The energy accumulation index is calculated based on the product basis of the equivalent pulse discharge intensity characteristics and the hydration conductivity factor within the current sampling period, as well as the approximate term of the first derivative of the product basis under continuous time variables. Based on the statistical distribution characteristics of the energy accumulation index within the time window and the baseline drift compensation amount, a warning threshold is dynamically generated. The energy accumulation index of the current sampling period is compared with the warning threshold. Based on the comparison results, the risk of pollution flashover is determined and a warning signal is output.

[0007] Preferably, acquiring the transient leakage current signal of the insulator over multiple consecutive sampling periods includes: The original grounding current is collected by a through-type high-frequency current transformer deployed at the grounding end of the insulator, and then input into a hardware bandpass filter to remove the power grid fundamental frequency component and background white noise. After being discretized by an analog-to-digital converter, the transient leakage current signal in the passband range is obtained.

[0008] Preferably, the equivalent pulse discharge intensity characteristic satisfies the expression: ; In the formula, Indicates the first Equivalent pulse discharge intensity characteristics for each sampling period; Indicates the sampling point number; This represents the total number of sampling points within each sampling period; Indicates the first Within the sampling period, the first The amplitude of the transient leakage current signal at each sampling point; This indicates the time interval between sampling points.

[0009] Preferably, the hydrated conductivity factor satisfies the following expression: ; In the formula, Indicates the first Hydrated conductivity factor per sampling period; Represents an exponential function with the natural constant as its base; Indicates the humidity sensitivity coefficient; Indicates the first Environmental humidity data within each sampling period; This represents the critical humidity parameter; This represents the ionization activation energy, expressed in J / mol. Represents the ideal gas constant; Indicates the reference test temperature; Indicates the first Kelvin absolute temperature converted from ambient temperature data within a sampling period.

[0010] Preferably, the energy accumulation index satisfies the expression: ; In the formula, Indicates the first Energy accumulation index for each sampling period; This represents the function that takes the maximum value. Indicates the first Equivalent pulse discharge intensity characteristics for each sampling period; Indicates the first Hydrated conductivity factor per sampling period; This represents the prediction time weighting coefficient; Indicates the first Equivalent pulse discharge intensity characteristics for each sampling period; Indicates the first Hydrated conductivity factor per sampling period.

[0011] Preferably, the dynamic generation of the early warning threshold based on the statistical distribution characteristics of the energy accumulation index within the time window and the benchmark drift compensation amount includes: The mean of the energy accumulation index within the continuous time window preceding the current sampling period is used as the warning mean for the current sampling period, and the standard deviation of the energy accumulation index preceding the current sampling period is used as the warning standard deviation for the current sampling period. A baseline drift compensation amount is constructed based on the difference between the warning mean values ​​of adjacent sampling periods. The warning threshold is obtained based on the warning mean value, warning standard deviation, and baseline drift compensation amount for the current sampling period.

[0012] Preferably, the warning threshold satisfies the expression: ; In the formula, Indicates the first The warning threshold for each sampling period; Indicates the first The average warning value for each sampling period; Indicates the first The standard deviation of the early warning for each sampling period; Indicates the first The average warning value for each sampling period; This is the baseline drift compensation amount; It is a minimum value function; It is the static upper limit constant of the ultimate breaking potential energy of the insulator.

[0013] Preferably, the determination of pollution flashover risk based on comparison results includes: If the energy accumulation index exceeds the warning threshold, it is determined that the insulator currently poses a high risk of flashover.

[0014] Preferably, the output warning signal includes: When it is determined that there is a high risk of flashover due to pollution, the underlying monitoring equipment immediately generates a flashover warning signal carrying the equipment identification code; the flashover warning signal and the over-limit status data are uploaded to the remote monitoring backend through the wireless communication network, and the remote monitoring backend maps the geographical coordinates based on the equipment identification code and issues a work order.

[0015] Secondly, the present invention provides an insulator pollution flashover risk early warning system based on multi-parameter fusion, including a processor and a memory. The memory stores computer program instructions, and when the computer program instructions are executed by the processor, the above-mentioned insulator pollution flashover risk early warning method based on multi-parameter fusion is implemented.

[0016] By adopting the above technical solution, a computer program is generated from the above-mentioned insulator pollution flashover risk early warning method based on multi-parameter fusion and stored in the memory so that it can be loaded and executed by the processor. In this way, a terminal device can be made based on the memory and the processor for convenient use.

[0017] The beneficial effects of this invention are as follows: This invention avoids steady-state noise interference by extracting the discrete energy characteristics of high-frequency transient pulses, and constructs a hydration conductivity factor based on changes in ambient temperature and humidity to reconstruct the catalytic process of water film expansion and ion migration. Subsequently, the equivalent pulse discharge intensity characteristics are multiplied with the hydration conductivity factor and superimposed with historical change trends to form an energy accumulation index reflecting the deterioration acceleration. At the same time, a dynamic early warning threshold is generated by superimposing a mean drift compensation term on the window statistical boundary, so that the monitoring boundary can smoothly follow the environmental benchmark. While filtering out daily microclimate fluctuations, it can keenly capture the sharp jump in partial discharge, thereby solving the problem of delayed response and frequent false alarms of fixed thresholds under complex operating conditions, and realizing early warning of insulator pollution flashover risk. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating an insulator pollution flashover risk early warning method based on multi-parameter fusion according to the present invention. Detailed Implementation

[0019] 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, not all, of the embodiments of the present invention. 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.

[0020] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0021] This invention discloses an insulator pollution flashover risk early warning method based on multi-parameter fusion, referring to... Figure 1 This includes steps S1-S3: S1: Acquire transient leakage current signal and ambient temperature and humidity data, and calculate the equivalent pulse discharge intensity characteristics.

[0022] It should be noted that during early partial discharge of an insulator, the leakage current on the surface exhibits high-frequency transient pulse characteristics, and the amplitude and duration of the pulse reflect the amount of physical energy released in a single discharge. Furthermore, industrial environments are characterized by strong power frequency electromagnetic interference and white noise, making it highly susceptible to errors if the original waveform is directly subjected to threshold judgment. Therefore, this invention first extracts the pure transient pulse through a filtering mechanism, and then calculates the transient leakage current signal, converting the discrete current pulse into a stable equivalent pulse discharge intensity characteristic that characterizes the discharge intensity. This provides fundamental data for subsequent assessment of the discharge destructive force and insulation degradation trend.

[0023] Specifically, the original grounding current is collected by a through-type high-frequency current transformer deployed at the grounding end of the insulator, and then input into a hardware bandpass filter to remove the fundamental frequency component of the power grid and background white noise. After discretization by an analog-to-digital converter, the transient leakage current signal is obtained. The bandpass filter cutoff frequency setting process is as follows: Since the energy of the discharge pulse is mainly concentrated in the high-frequency band at the megahertz level, while the normal operating current of the power grid is a low-frequency component of 50 Hz, this embodiment sets the low-frequency cutoff frequency of the hardware bandpass filter to 1 MHz and the high-frequency cutoff frequency to 30 MHz, so that the transient discharge signal within this passband range can pass through without loss, while physically isolating the 50 Hz fundamental frequency component of the power grid and background white noise in other frequency bands.

[0024] Simultaneously, the current air quality is collected by miniature weather stations deployed around the insulators, and environmental humidity and temperature data are obtained.

[0025] Furthermore, considering both the physical response time of partial discharge channel development and the data throughput load of the edge monitoring terminal, the continuous operating time is divided into multiple sampling periods of fixed length. In this embodiment, the fixed length of the sampling period is set to 1 second, which covers 50 power grid frequency cycles. This time span can not only fully capture the transient energy accumulation process of a single pollution flashover, but also avoid calculation delays caused by high-frequency data accumulation. In other embodiments, implementers can adaptively adjust the sampling period according to the length of the insulator string and the reporting frequency of the communication module.

[0026] The equivalent pulse discharge intensity characteristics for each sampling period are obtained based on the transient leakage current signal: ; In the formula, Indicates the first Equivalent pulse discharge intensity characteristics for each sampling period; Indicates the sampling point number; This represents the total number of sampling points within each sampling period; Indicates the first Within the sampling period, the first The amplitude of the transient leakage current signal at each sampling point; This indicates the time interval between sampling points.

[0027] When the surface of an insulator becomes damp and contaminated, causing severe distortion of the local electric field, it can trigger intermittent weak corona discharges, which manifest as the amplitude of the transient leakage current signal. The appearance of extremely short, high-frequency spike pulses, within the equivalent conductive path formed by contamination and moisture on the insulator surface, results in a thermal effect and electrical stress intensity that are positively correlated with the square of the current amplitude. This invention approximates the instantaneous power of the leakage current signal by squaring the current amplitude at each discrete sampling point and multiplying it by the sampling interval. Essentially, it integrates the instantaneous power of the leakage current signal in the discrete time domain. As the local discharge activity on the insulator surface gradually intensifies, the amplitude of a single pulse increases, or the frequency of high-frequency discharges increases, the amplitude of the transient leakage current signal... Tiny electrical abrupt changes can be drastically amplified, resulting in a significant increase in the equivalent pulse discharge intensity characteristics. This significantly increases the potential energy of the insulator, thereby transforming the hidden and difficult-to-capture transient discharge pulse into a quantitative indicator that can intuitively measure the accumulated destructive potential energy of the partial discharge on the insulator surface, effectively amplifying the subtle degradation characteristics in the early stages of the evolution from a stable insulation state to a local arcing state.

[0028] S2: Construct a hydration conductivity factor that maps the synergistic catalytic effect of temperature and humidity, and calculate the energy accumulation index based on the product basis of the equivalent pulse discharge intensity characteristics and the hydration conductivity factor and its first derivative approximation term.

[0029] It should be noted that the conductivity of the contamination layer on the insulator surface is not a single variable, but is governed by two independent physical mechanisms: moisture condensation and temperature-induced degradation. High humidity promotes the deliquescence of soluble salts to form a continuous water film, while increased temperature accelerates the migration rate of conductive ions within the water film. Both factors amplify the destructive effect of leakage pulses. Therefore, this invention constructs a hydration conductivity factor to map the objective catalytic effect of temperature and humidity on contamination conductivity, and integrates it with the equivalent pulse discharge intensity characteristics to construct an energy accumulation index that truly reflects the degree of damage to the insulator as it evolves into localized arcing.

[0030] Specifically, soluble salts on the surface of insulators undergo phase change deliquescence under specific air humidity conditions, forming a conductive water film. To accurately define the triggering boundary of this physical process, this invention establishes a standardized critical parameter calibration procedure: First, surface contamination samples from the area where the insulator is located are pre-extracted for equivalent salt density testing and composition analysis to clarify the chemical properties of the main contaminating salts. Then, combined with historical meteorological evolution statistics for the same period in the region, the humidity range of water absorption phase change for different salt components under natural conditions is cross-compared. Based on extensive field measurements and physical property databases, it is known that common insulator contamination salts in nature begin to deliquinate rapidly when the relative humidity reaches 70% to 85%. To balance versatility and computational stability, this embodiment uses a critical humidity parameter... The default setting is 75% to accurately anchor the objective physical boundary of hydration initiation, effectively avoiding misjudging a safe state in a low-humidity environment as a high-risk state. If the on-site pollutant composition is special or the environmental climate characteristics deviate from the norm, the implementers can strictly calibrate and set the critical humidity parameter according to the actual phase change humidity range obtained from the aforementioned testing and statistical procedures.

[0031] Furthermore, according to the classical Arrhenius theorem in physical chemistry, the evolution of the conductivity ion mobility in an electrolyte solution with thermodynamic temperature satisfies the following expression: ; In the formula, Indicates ionic conductivity; Indicates the pre-exponential factor; Represents an exponential function with the natural constant as its base; Indicates the ionization activation energy; Represents the ideal gas constant; This represents absolute temperature. To eliminate the exponential factor under different test conditions. To eliminate absolute value interference and achieve standardized mapping of conductivity across multiple environments, this invention introduces a benchmark normalization mechanism. The specific derivation process is as follows: The benchmark test temperature under the standard reference state is set to... Its corresponding reference conductivity is ; Current ambient temperature Corresponding instantaneous conductivity The relative conductivity multiplier is obtained by performing a physical ratio calculation with the reference conductivity. Eliminating the constant term through algebraic simplification And by using the exponential arithmetic rules to extract the exponential difference term, the temperature excitation multiplier term is obtained as follows: Simultaneously, since the absolute temperature in the Arrhenius equation must be calculated based on the thermodynamic temperature scale, and field micro-weather stations usually output Celsius temperature scale data directly, this invention converts the collected Celsius ambient temperature data into Kelvin absolute temperature.

[0032] Based on the kinetics of deliquescence of pollutants and salts, when the air humidity exceeds the critical phase transition point, the water film expansion rate exhibits an approximately exponential relationship with the supercritical humidity difference. Therefore, this invention utilizes a humidity-sensitive index term. The nonlinear catalytic amplification effect characterizing water condensation diffusion, wherein, This represents the humidity sensitivity coefficient, with units of 1000 ppm. , Indicates the first Environmental humidity data within each sampling period, This represents the critical humidity parameter.

[0033] Furthermore, the humidity sensitivity index, which characterizes moisture condensation and diffusion, is physically multiplied with the temperature excitation multiplier, which characterizes ion mobility, to obtain the hydration conductivity factor for each sampling period: ; In the formula, Indicates the first Hydrated conductivity factor per sampling period; Represents an exponential function with the natural constant as its base; Indicates the humidity sensitivity coefficient; Indicates the first Environmental humidity data within each sampling period; This represents the critical humidity parameter; This represents the ionization activation energy, expressed in J / mol. Represents the ideal gas constant; Indicates the reference test temperature; Indicates the first Kelvin absolute temperature converted from ambient temperature data within a sampling period. When ambient humidity data... Exceeding the critical humidity parameter And when the ambient temperature rises, The increase in the value promotes the hydration conductivity factor It exhibits exponential multiplication, strictly adhering to the fundamental laws of thermodynamics, and converts climate parameters into physical multipliers that map the degradation of insulation performance.

[0034] When ambient humidity data Exceeding the critical phase transition threshold At that time, supercritical humidity difference The water film spreads exponentially, causing the humidity sensitivity index to increase. Rapidly rising; synchronously, with the ambient temperature As the temperature increases, the temperature-induced multiplier term increases with ambient temperature. Monotonically increasing. The humidity sensitivity index and the temperature-excited multiplier term physically characterize the phase transition catalysis of moisture deliquescence and the accelerated migration of ions through thermal motion, respectively. Their product is not a simple linear superposition, but rather constitutes a synergistic amplification of temperature and humidity. Under the effect of this product, the hydration conductivity factor... It increases exponentially as the microclimate deteriorates.

[0035] In this embodiment, key physical property parameters are obtained through a standardized laboratory calibration process: First, typical contamination samples are extracted from the insulator surface to prepare standard test pieces, which are then placed in a high-precision constant temperature and humidity chamber. The ambient humidity is adjusted in steps at a reference temperature of 298.15 Kelvin while simultaneously recording the surface equivalent conductivity data. The exponential growth curve of the humidity supercritical segment is fitted using the nonlinear least squares method, and the fitted parameter of the exponential growth rate is used as the humidity sensitivity coefficient. In this embodiment, the empirical value is 0.05. Subsequently, the ambient humidity was fixed at a high humidity saturation state of 85%, and the temperature was gradually adjusted within the range of 278.15 Kelvin to 318.15 Kelvin while the corresponding conductivity was collected. The conductivity was then determined based on the logarithmic linearized form of the Arrhenius equation. draw and The scatter plot of the relationship was used to calculate the absolute value of the slope through linear regression and multiplied by the ideal gas constant to calibrate the ionization activation energy. In this embodiment, the ionization activation energy The empirical value is 15000 J / mol.

[0036] By combining the equivalent pulse discharge intensity characteristics and the hydration conductivity factor of each sampling period, the destructive potential energy of local arcing on the insulator surface is evaluated. Specifically: Since insulation degradation is not a static mapping but a dynamic evolution process with thermodynamic inertia, simply reflecting the absolute energy at the current moment is insufficient for early warning. Therefore, this invention introduces the first-order predictive physics principle of Taylor expansion, using the current state plus the transient rate of change to predict the destructive force of the evolution at the next moment. Let the characteristic of the local effective discharge intensity in the current sampling period be... This is used to characterize the relative destructive potential base after environmental catalysis; based on the first-order Taylor expansion: In the formula, Represents a continuous-time variable; Indicates the physical look-ahead time step; The function representing the discharge intensity at the current moment; This represents the first derivative of the function with respect to time, i.e., the instantaneous rate of change. In the discrete-time domain, it represents the first derivative term of a continuous physical state. backward difference is available By performing a high-precision approximation substitution and substituting it into the expansion, we can obtain the predicted future. The approximate expression for the energy state at time t is: To reduce the real-time computing overhead of the underlying embedded control system and avoid frequent processing of small time variables, this invention uses the physical look-ahead time constant. With sampling interval The ratio is abstracted as a dimensionless prediction time weighting coefficient. Substituting the above approximation into the equation and performing algebraic simplification, and introducing a non-negative boundary cutoff function to eliminate transient negative fluctuations during the calculation process, the energy accumulation index for each sampling period is finally derived to satisfy the following expression: ; In the formula, Indicates the first Energy accumulation index for each sampling period; This represents the function that takes the maximum value. Indicates the first Equivalent pulse discharge intensity characteristics for each sampling period; Indicates the first Hydrated conductivity factor per sampling period; This represents the prediction time weighting coefficient; Indicates the first Equivalent pulse discharge intensity characteristics for each sampling period; Indicates the first Hydrated conductivity factor per sampling period. The substrate characterizes the instantaneous discharge intensity after environmental catalysis within the current cycle. This establishes a forward tracking mechanism for the rate of change of discrete-time series. The evolution of an insulator from steady micro-discharge to local arcing is often accompanied by a step-like surge in energy release. At this point, the backward difference term... It will rapidly change from a flat trend to a positive jump, and after being amplified by the prediction time weighting coefficient, it will be linearly superimposed with the base strength, resulting in an energy accumulation index. It exhibits high sensitivity to degradation acceleration.

[0037] In this embodiment, by collecting historical pollution flashover fault evolution sequence data of the target power grid area, a priori sample library containing discharge intensity mutation characteristics is constructed. Grid search and cross-validation are performed with the goal of maximizing early warning accuracy. After dynamic calibration, the prediction time weight coefficient is set to 2. In other embodiments, the implementer can set the weight coefficient according to the ratio of the relaxation time constant of the measured pollution discharge channel expansion to the sampling interval.

[0038] S3: Based on the statistical distribution characteristics of the energy accumulation index within the time window and the baseline drift compensation, a warning threshold is dynamically generated to determine the risk of pollution flashover and output a warning signal.

[0039] It should be noted that due to the alternation of day and night and seasonal changes in the operating environment of insulators, the background leakage energy level is in a state of continuous dynamic fluctuation. If we rely on manually preset absolute values ​​as alarm boundaries, it is easy to generate false alarms when the environment fluctuates naturally, or to miss alarms when the microclimate deteriorates slowly. Therefore, this invention utilizes the statistical distribution characteristics of the energy accumulation index within a local time window, combined with the real-time steady-state reference drift, to generate a warning threshold.

[0040] Specifically, in order to filter out the interference of occasional high-frequency electromagnetic thermal noise while retaining the energy accumulation trend with physical deterioration significance, the time window length is obtained based on the time constant required for the thermal conduction of the insulator surface skirts to reach dynamic equilibrium. The thermodynamic equilibrium period of the insulator surface usually covers 20 to 50 sampling periods. In this embodiment, the time window length is set to 30 to ensure that the multiple sets of continuous data contained in the window can truly represent the benchmark evolution law of the current steady-state background of the insulator. In other embodiments, the implementer can set the time window length according to the heat capacity parameters of the specific insulator material.

[0041] Furthermore, based on historical indicator data within the time window, the first... The mean and standard deviation of the early warning for each sampling period: ; ; In the formula, Indicates the first The average warning value for each sampling period; Indicates the length of the time window; Indicates the sampling sequence number within the time window; Indicates the first Energy accumulation index for each sampling period; Indicates the first The standard deviation of the early warning for each sampling period.

[0042] By combining the warning mean and warning standard deviation of each sampling period, the first warning is calculated. The warning threshold for each sampling period is as follows: According to the principles of statistical process control, the natural fluctuation boundary of a system is usually determined by the mean plus a multiple of the standard deviation. However, the changing microclimate environment of the insulator leads to a slow and continuous drift of the thermodynamic reference, and a simple static limit boundary cannot adapt to the constantly evolving background. Therefore, this invention introduces a time-series reference drift compensation mechanism based on the steady-state fluctuation boundary. The environmental evolution rate of the insulator background state within a unit sampling period can be equivalent to the algebraic difference between the current period's warning mean and the previous period's warning mean. This invention uses this physical difference as an additional safety compensation term, directly superimposed on the basic control upper limit, to obtain the warning threshold. The warning threshold satisfies the expression: ; In the formula, Indicates the first The warning threshold for each sampling period; Indicates the first The average warning value for each sampling period; Indicates the first The standard deviation of the early warning for each sampling period; Indicates the first The average warning value for each sampling period; It is a minimum value function. This constitutes the absolute physical tolerance boundary that includes natural white noise from the environment. The physical and dynamic drift velocity characterizes the historical evolution of the background environment. As the overall environment of the insulator slowly deteriorates, the current warning average gradually increases, and the drift velocity term moderately raises the warning threshold. To adapt to normal physical disturbances and effectively reduce false alarms caused by the slow rise of the background reference. The static upper limit constant of the insulator's ultimate breaking potential energy is pre-written into the system's underlying memory. The specific setup method is as follows: Apply the highest operating phase voltage of the system to insulators of the same model in an artificial climate chamber to conduct artificial pollution-approach flashover tests under extreme conditions; simultaneously collect transient leakage current and temperature / humidity data of the insulator within multiple consecutive standard time windows before the critical arc initiation, substitute these data into the aforementioned model to calculate the extreme value distribution of the energy accumulation index under stable arcing conditions; extract the lower quartile of this extreme value distribution, multiply it by an engineering safety margin coefficient of 0.8 to 0.9, and pre-burn the converted result into the underlying firmware as the static upper limit constant of the insulator's ultimate failure potential energy. This invention employs an additive dynamic compensation mechanism, effectively eliminating the potential for delayed early warning caused by threshold rigidity. By limiting the absolute red line through a minimum value function, it also prevents long-term degradation trends from being masked by the drift compensation mechanism, ensuring the accuracy of the monitoring system's early warning under complex operating conditions.

[0043] Furthermore, the first Energy accumulation index per sampling period With the Early warning threshold for each sampling period Perform a single-value comparison; if the energy accumulation index... Greater than the warning threshold If the insulator is found to be at high risk of flashover, the underlying monitoring equipment will immediately generate a flashover warning signal carrying the equipment identification code and upload the warning signal and over-limit status data to the remote monitoring backend via the wireless communication network. The backend will then map the geographical coordinates based on the equipment identification code and issue a work order. Otherwise, the insulator is considered to be operating stably.

[0044] This invention also discloses an insulator pollution flashover risk early warning system based on multi-parameter fusion, including a processor and a memory. The memory stores computer program instructions, which, when executed by the processor, implement an insulator pollution flashover risk early warning method based on multi-parameter fusion according to the present invention.

[0045] The system also includes other components well known to those skilled in the art, such as communication buses and communication interfaces, the settings and functions of which are known in the art and will not be described in detail here.

[0046] In the description of this specification, "multiple" or "several" means at least two, such as two, three or more, unless otherwise expressly and specifically defined.

[0047] While this specification has shown and described numerous embodiments of the invention, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Many modifications, alterations, and alternatives will occur to those skilled in the art without departing from the spirit and essence of the invention. It should be understood that various alternatives to the embodiments of the invention described herein may be employed in the practice of this invention.

Claims

1. A multi-parameter fusion-based insulator pollution flashover risk early warning method, characterized in that, include: The transient leakage current signal of the insulator and the ambient temperature and humidity data are acquired in multiple consecutive sampling periods; the instantaneous power of the transient leakage current signal is approximated by integration in the discrete time domain to obtain the equivalent pulse discharge intensity characteristics that characterize the partial discharge intensity in each sampling period. Based on environmental temperature and humidity data, a hydration conductivity factor that maps the synergistic catalytic effect of temperature and humidity was constructed. The energy accumulation index is calculated based on the product basis of the equivalent pulse discharge intensity characteristics and the hydration conductivity factor within the current sampling period, as well as the approximate term of the first derivative of the product basis under continuous time variables. Based on the statistical distribution characteristics of the energy accumulation index within the time window and the baseline drift compensation amount, a warning threshold is dynamically generated. The energy accumulation index of the current sampling period is compared with the warning threshold. Based on the comparison results, the risk of pollution flashover is determined and a warning signal is output.

2. The insulator pollution flashover risk early warning method based on multi-parameter fusion according to claim 1, characterized in that, The acquisition of the transient leakage current signal of the insulator over multiple consecutive sampling periods includes: The original grounding current is collected by a through-type high-frequency current transformer deployed at the grounding end of the insulator, and then input into a hardware bandpass filter to remove the power grid fundamental frequency component and background white noise. After being discretized by an analog-to-digital converter, the transient leakage current signal in the passband range is obtained.

3. The insulator pollution flashover risk early warning method based on multi-parameter fusion according to claim 1, characterized in that, The equivalent pulse discharge intensity characteristic satisfies the expression: ； In the formula, Indicates the first Equivalent pulse discharge intensity characteristics for each sampling period; Indicates the sampling point number; This represents the total number of sampling points within each sampling period; Indicates the first Within the sampling period, the first The amplitude of the transient leakage current signal at each sampling point; This indicates the time interval between sampling points.

4. The insulator pollution flashover risk early warning method based on multi-parameter fusion according to claim 1, characterized in that, The hydrated conductivity factor satisfies the expression: ； In the formula, Indicates the first Hydrated conductivity factor per sampling period; Represents an exponential function with the natural constant as its base; Indicates the humidity sensitivity coefficient; Indicates the first Environmental humidity data within each sampling period; This represents the critical humidity parameter; This represents the ionization activation energy, expressed in J / mol. Represents the ideal gas constant; Indicates the reference test temperature; Indicates the first Kelvin absolute temperature converted from ambient temperature data within a sampling period.

5. The insulator flashover risk early warning method based on multi-parameter fusion according to claim 1, characterized in that, The energy accumulation index satisfies the expression: ； In the formula, Indicates the first Energy accumulation index for each sampling period; This represents the function that takes the maximum value. Indicates the first Equivalent pulse discharge intensity characteristics for each sampling period; Indicates the first Hydrated conductivity factor per sampling period; This represents the prediction time weighting coefficient; Indicates the first Equivalent pulse discharge intensity characteristics for each sampling period; Indicates the first Hydrated conductivity factor per sampling period.

6. The insulator pollution flashover risk early warning method based on multi-parameter fusion according to claim 1, characterized in that, The method for dynamically generating early warning thresholds based on the statistical distribution characteristics of the energy accumulation index within a time window and the baseline drift compensation includes: The mean of the energy accumulation index within the continuous time window preceding the current sampling period is used as the warning mean for the current sampling period, and the standard deviation of the energy accumulation index preceding the current sampling period is used as the warning standard deviation for the current sampling period. A baseline drift compensation amount is constructed based on the difference between the warning mean values ​​of adjacent sampling periods. The warning threshold is obtained based on the warning mean value, warning standard deviation, and baseline drift compensation amount for the current sampling period.

7. The insulator flashover risk early warning method based on multi-parameter fusion according to claim 6, characterized in that, The warning threshold satisfies the expression: ； In the formula, Indicates the first The warning threshold for each sampling period; Indicates the first The average warning value for each sampling period; Indicates the first The standard deviation of the early warning for each sampling period; Indicates the first The average warning value for each sampling period; This is the baseline drift compensation amount; It is a minimum value function; It is the static upper limit constant of the ultimate breaking potential energy of the insulator.

8. The insulator flashover risk early warning method based on multi-parameter fusion according to claim 1, characterized in that, The determination of pollution flashover risk based on comparison results includes: If the energy accumulation index exceeds the warning threshold, it is determined that the insulator currently poses a high risk of flashover.

9. The insulator flashover risk early warning method based on multi-parameter fusion according to claim 8, characterized in that, Output warning signals, including: When it is determined that there is a high risk of flashover due to pollution, the underlying monitoring equipment immediately generates a flashover warning signal carrying the equipment identification code; the flashover warning signal and the over-limit status data are uploaded to the remote monitoring backend through the wireless communication network, and the remote monitoring backend maps the geographical coordinates based on the equipment identification code and issues a work order.

10. An insulator pollution flashover risk early warning system based on multi-parameter fusion, characterized in that, include: A processor and a memory, wherein the memory stores computer program instructions that, when executed by the processor, implement an insulator pollution flashover risk early warning method based on multi-parameter fusion according to any one of claims 1-9.

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