A method and system for determining a moment of tree fault fire of a power distribution overhead conductor

Abstract

This invention discloses a method and system for determining the ignition time of a power distribution overhead conductor igniting after contacting a tree. The method includes the following steps: setting up an experimental environment and collecting full-process data in the experimental environment at a preset sampling frequency; obtaining the initial moisture content of the experimental trees, calculating the heat absorption and mass of water evaporation of the tree model, updating the tree moisture content, and saving it in time alignment; fitting the relationship between the tree conductivity, moisture content, and temperature throughout the entire process to obtain a conductivity function; using the conductivity function to construct a simulated resistance curve based on the tree moisture content and temperature, and using the voltage and current data collected in the experimental environment to construct a measured resistance curve; comparing the simulated resistance curve and the measured resistance curve, and determining the moment when the simulated resistance curve and the measured resistance curve show a clear bifurcation as the moment of open flame. This invention has a wide range of applications, low cost and maintenance difficulty, and ensures high accuracy.

Description

Technical Field

[0001] This invention belongs to the field of power distribution network fault analysis technology, and specifically relates to a method and system for determining the ignition time of a tree-touching fault in overhead power distribution conductors. Background Technology

[0002] When medium-voltage overhead power lines traverse forest areas, the risk of conductors contacting trees is very high. These faults are characterized by high transition resistance and a high probability of ignition, easily leading to forest fires and causing serious safety hazards and property damage. For example, the "Black Saturday" fires in Victoria, Australia in 2009 and the forest fires in California, USA in 2018 were both confirmed to be related to conductor contact with trees. According to data from SCE's 2019 WMP program annual report, among 302 electrical fire reports from 2015 to 2017, 92% involved medium-voltage power distribution systems, with fires caused by conductors contacting trees accounting for 17% of all electrical fires.

[0003] Current detection methods for TSF (Tree-contact Single-phase-to-ground Faults) typically classify them as ordinary HIF (High Impedance Faults) and treat them accordingly. Existing literature has explored fault detection through analysis of the frequency domain characteristics and composite features of zero-sequence electrical quantities. For example, some studies propose determining faults by the slope of the interval curve of the zero-sequence current waveform, while others use the differential method to establish a waveform slope anomaly index, utilizing the fundamental frequency and harmonics of the zero-sequence current to determine the occurrence of HIFs. Although these methods can identify certain types of faults, their sensitivity still falls short of the requirements for TSF detection. Another approach employs artificial intelligence technology for fault identification, analyzing the distortion characteristics of the HIF zero-sequence current, using ensemble learning algorithms to identify faults, or combining convolutional neural networks to analyze traveling wave signals.

[0004] Chinese invention patent application CN118797504A discloses a phased identification method based on the evolution process of a single-phase conductor contacting a tree to ground fault. The method includes the following steps: collecting initial distribution network line data and phenomenon video of the entire process of a single-phase conductor contacting a tree to ground fault; dividing the initial distribution network line data into four fault stages and one normal stage dataset based on the time points of the phenomenon video; preprocessing the dataset to obtain intermediate distribution network line data; establishing an initial fault development and evolution identification model based on a DICNN network model and training it to obtain a final fault development and evolution identification model; setting the final fault development and evolution identification model at the distribution network line terminal, and identifying whether a tree-line contact fault has occurred and the stage to which the fault has developed by detecting the distribution network line data.

[0005] While the aforementioned methods have certain advantages, their versatility in practical applications cannot be guaranteed due to the limited sample size of faults. Current research on TSF primarily focuses on fault detection and electrical characteristic analysis, but accurate estimation of the fault occurrence time has not received sufficient attention. Furthermore, traditional fault detection methods do not adequately consider key physical processes such as tree moisture content, water evaporation during temperature rise, and carbonization, making it difficult for the system to accurately identify critical change points before ignition. Summary of the Invention

[0006] This invention provides a method and system for determining the ignition time of a fire caused by a tree contact fault in an overhead power distribution conductor, aiming to solve the problems of system complexity, low versatility, and inaccurate prediction of ignition time in existing technologies.

[0007] This invention establishes a dynamic fault model based on real-time monitoring by combining key physical parameters of trees. This model accurately estimates the ignition time of a single-phase ground fault in a tree, reducing errors associated with traditional temperature or current threshold methods. Compared to artificial intelligence methods, it effectively reduces system, computational, and training costs. The fault model considers physical processes such as moisture evaporation and tree carbonization during temperature rise. By analyzing the heat transfer process of the tree in stages, it can accurately identify key nodes before ignition, such as the rise and inflection of the fault current, providing precise estimates of the ignition time and offering technical support for timely fire prevention responses.

[0008] To solve the above-mentioned technical problems, the determination method proposed in this invention includes the following steps:

[0009] An experimental environment was set up to simulate the entire process of a power distribution overhead conductor touching a tree, and data of the entire process was collected in the experimental environment at a preset sampling frequency.

[0010] The initial moisture content of the experimental trees was obtained, and the complete process data was continuously collected and analyzed over time during the experiment to generate real-time data.

[0011] The heat absorbed by water evaporation in the tree model is calculated based on real-time data. Then, the mass of water evaporation is calculated based on the heat absorbed by water evaporation. The water evaporation mass is used to update the tree moisture content and is saved in time alignment.

[0012] Based on real-time data, aligned tree moisture content, and voltage and current data collected in the experimental environment, the relationship between tree conductivity, moisture content, and temperature throughout the entire process is fitted to obtain the conductivity function.

[0013] The conductivity function is used to construct a simulated resistance curve based on the tree's water content and temperature, while the voltage and current data collected in the experimental environment are used to construct a measured resistance curve.

[0014] By comparing the simulated resistance curve and the measured resistance curve, the moment when the simulated resistance curve and the measured resistance curve show a clear divergence is determined as the moment when an open flame appears.

[0015] Preferably, the experimental environment includes a neutral point ungrounded simulation section, a conductor-to-tree simulation section, and a data acquisition section; the neutral point ungrounded simulation section is a energized three-phase overhead conductor; the conductor-to-tree simulation section includes trees transplanted to the test site, with one phase drawn from the three-phase overhead conductor and connected to the tree; the data acquisition section continuously records the phase voltage and grounding current throughout the entire process, records the experimental phenomena during the ignition process, records the temperature changes of the tree, until the discharge channel penetrates the vegetation and causes a short circuit.

[0016] Preferably, the full-process data includes conductor phase voltage, current passing through the experimental tree, and temperature of the experimental tree.

[0017] Preferably, the method for obtaining the initial moisture content includes experimental weighing and preset values;

[0018] The formula for calculating the experimental weight is:

[0019]

[0020] In the formula, m s m0 represents the fresh weight of the wood block obtained from the experimental sampling, and m0 represents the oven-dry weight of the wood block.

[0021] The preset values ​​are derived from existing data on the corresponding tree species in the experimental field during the experimental season.

[0022] Preferably, the experimental process includes, in sequence, the tree temperature rise stage, the water evaporation stage, the carbonization development stage, and the open flame flashover stage.

[0023] Preferably, the method for determining obvious bifurcation includes the difference index determination method and the visualization analysis method;

[0024] The difference index is a relative index, and its calculation method is as follows:

[0025]

[0026] In the formula, Δy t Here, y1(t) represents the difference index at time t, y2(t) represents the resistance value corresponding to the simulated resistance curve at time t, and y2(t) represents the resistance value corresponding to the measured resistance curve at time t. ∈ is a preset parameter used to avoid the denominator being zero.

[0027] When Δy t When the preset threshold is exceeded, it is determined that the simulated resistance curve and the measured resistance curve show a clear divergence.

[0028] Preferably, the relationship between electrical conductivity, moisture content, and temperature of the trees throughout the entire process is fitted using the least squares method. The fitted relationship between electrical conductivity and temperature and moisture content is expressed as follows:

[0029] lnσ t (W,T)=7.458W+0.057T-0.050W·T-10.754

[0030] In the formula, σ t (W,T) represents the electrical conductivity calculated at time t relative to temperature and moisture content, where W is the moisture content of the tree and T is the temperature of the tree.

[0031] Preferably, the formula for calculating the resistance in the resistance simulation curve is:

[0032]

[0033] In the formula, n is the level of the line in the tree model, l0 is the length of the basic branch in the tree model, i.e. the height of the trunk, and r0 is the radius of the basic branch, i.e. the radius of the trunk.

[0034] The tree model is a fractal network model simplified from the morphology of experimental trees. In the tree model, α and β are defined as the ratio of the length of the branches in the (k+1)th layer network and the ratio of the radius of the branches in the kth layer network, respectively, as follows:

[0035]

[0036] In the formula, l k l k+1 These are the branch lengths of the k-th layer network and the (k+1)-th layer network, respectively, r k r l+1 These are the tree radii of the k-th layer network and the tree radii of the (k+1)-th layer network, respectively.

[0037] Preferably, the method for calculating the mass of water evaporated is as follows:

[0038] Calculate the total heat generated Q by the current passing through the tree at time t. s :

[0039]

[0040] In the formula, U is the phase voltage of the conductor connected to the tree;

[0041] The heat dissipation and absorption of trees include convective heat dissipation, radiative heat dissipation, heat absorption due to temperature rise, and heat absorption due to water evaporation. The total heat output, after deducting convective and radiative heat dissipation, represents the total heat absorption. The product of the total heat absorption and the evaporation absorption ratio is the heat absorption due to water evaporation, expressed as follows:

[0042] Q w =(Q s -Q c -Q r )·k f

[0043] k f = (1+e) 98-T ) -1

[0044] In the formula, Q w As water evaporates and absorbs heat, Q s Q represents the total heat production. c For convective heat dissipation, Q r k represents the heat dissipation due to radiation. f Here, T is the evaporation absorption ratio coefficient, and T is the tree temperature.

[0045] Calculate the mass of water evaporated based on the heat absorbed during water evaporation:

[0046]

[0047] In the formula, Δm is the mass of water evaporated, and T w The temperature of the water.

[0048] In another aspect, the present invention also proposes a system for determining the timing of a fire caused by a tree contact fault in an overhead power distribution conductor. This system is used to implement the aforementioned determination method and includes:

[0049] The experimental environment module is used to simulate the entire process of a power distribution overhead conductor touching a tree fault, including a neutral point ungrounded simulation section and a conductor touching a tree simulation section.

[0050] The parameter acquisition module further includes: a voltage and current acquisition unit for acquiring phase voltage and grounding current data in the experimental environment in a time-aligned manner; and a temperature acquisition unit for acquiring the temperature of trees during the experiment and saving it in a time-aligned manner.

[0051] The data processing module further includes: a water evaporation calculation unit, used to calculate the heat absorbed by water evaporation of the tree model based on real-time collected data, and thereby calculate the water evaporation mass, used to update the real-time water content of the tree; and an electrical conductivity fitting unit, used to fit the relationship between the tree's electrical conductivity, water content and temperature based on experimental data, and generate an electrical conductivity function.

[0052] The resistance curve generation module further includes: a resistance simulation curve construction unit, used to construct a resistance simulation curve based on the conductivity function and the water content and temperature of the tree; and a resistance measurement curve construction unit, used to construct a resistance measurement curve based on voltage and current data collected in the experimental environment.

[0053] The determination module is used to compare the simulated resistance curve with the measured resistance curve and determine the moment when the simulated resistance curve and the measured resistance curve clearly diverge as the moment when an open flame appears.

[0054] Compared with the prior art, the present invention has the following technical effects:

[0055] 1. In the judgment method proposed in this invention, the fault model considers physical processes such as water evaporation and tree carbonization during the temperature rise process. By analyzing the heat transfer process of trees in stages, it can accurately identify key nodes before the fire, such as the rise and turning of the fault current, and provide accurate estimates of the fire time. This provides technical support for timely fire prevention response and can better meet the needs of fire process inversion and responsibility determination.

[0056] 2. The determination method proposed in this invention incorporates external environmental parameters such as temperature and humidity into the model in real time and dynamically adjusts the calculation conditions, enabling the method to adapt to the prediction of fault ignition time under different seasons and humidity conditions, thereby improving the applicability and prediction accuracy of the system.

[0057] 3. The judgment method proposed in this invention reflects the changes in actual electrical characteristics during the fault process by iteratively calculating variables such as conductivity, resistance, and temperature. Through closed-loop calculation of the model, the dynamic changes of various parameters over time can be tracked in real time, making the estimation of the fire time more consistent with the actual situation.

[0058] 4. The determination method proposed in this invention is based on physical models and experimental data, utilizing well-defined relationships between conductivity, moisture content, and temperature, as well as resistance change characteristics for analysis. Its theoretical foundation is clear, facilitating verification and interpretation. Compared to the black-box nature of artificial intelligence models, this method is more easily applied to engineering practice. Furthermore, it does not rely on large-scale training data, thus providing reliable results even with limited data.

[0059] 5. The judgment method proposed in this invention can flexibly adjust parameters according to experimental conditions and tree characteristics. Compared with artificial intelligence models, which need to be trained and optimized for specific application scenarios and have poor transferability, this invention has a wider range of applications.

[0060] 6. The determination method proposed in this invention mainly relies on experimental data and simple fitting calculations, without the need for complex computing resources and high-performance hardware support, which can effectively reduce costs and maintenance difficulties. Attached Figure Description

[0061] Figure 1 This is a flowchart illustrating the determination method described in this invention;

[0062] Figure 2 This is a schematic diagram of the full-scale experimental platform described in an embodiment of the present invention;

[0063] Figure 3 This is a simplified diagram of a fractal tree according to an embodiment of the present invention;

[0064] Figure 4 This is a flowchart of the iterative calculation described in an embodiment of the present invention;

[0065] Figure 5 This is a preview image of the effect described in the embodiment of the present invention;

[0066] Figure 6 This is another preview image of the effect described in an embodiment of the present invention. Detailed Implementation

[0067] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with specific embodiments of the present application and with reference to the accompanying drawings.

[0068] Example 1

[0069] This embodiment describes a method for determining the timing of a fire caused by a tree contact fault in an overhead power distribution conductor. Figure 1 As shown, it includes the following steps one through six:

[0070] Step one: Set up an experimental environment to simulate the entire process of a power distribution overhead conductor touching a tree. Collect data throughout the entire process in the experimental environment at a preset sampling frequency. The data includes conductor phase voltage, current passing through the experimental tree, and the temperature of the experimental tree.

[0071] To observe experimental phenomena and summarize patterns, a TSF full-scale experimental platform was built, such as... Figure 2As shown. The experimental environment includes three main parts: a neutral point ungrounded simulation section, a conductor-to-tree simulation section, and a data acquisition section. The neutral point ungrounded simulation section consists of a energized three-phase overhead conductor; in this embodiment, a 10kV line is used. The conductor-to-tree simulation section includes trees transplanted to the test site, with conductors from any one of the three-phase overhead conductors (A, B, and C) connected to the trees transplanted to the test site. The data acquisition section continuously records the phase voltage and grounding current throughout the entire TSF process, recording the phase voltage and grounding current from the start of energization. The phase voltage uses... Figure 2 Medium voltage sensor recording, grounding current used Figure 2 The experiment used a current sensor to record the entire ignition process, a high-definition camera to record the phenomena, and a thermal imaging thermometer to record the temperature changes of the trees until the discharge channel penetrated the vegetation and caused a short circuit.

[0072] Step two: Obtain the initial moisture content of the experimental trees, continuously collect and analyze the complete process data over time during the experiment, and generate real-time data.

[0073] The method for obtaining the initial moisture content includes experimental weighing and preset values;

[0074] The formula for calculating the experimental weight is:

[0075]

[0076] In the formula, m s m0 represents the fresh weight of the wood block obtained from the experimental sampling, and m0 represents the oven-dry weight of the wood block.

[0077] The preset values ​​are derived from existing data on the corresponding tree species in the experimental site during the experimental season. For example, they can be measured in advance by measuring different tree species in different seasons in the local area, or by directly using research data on local tree species from relevant departments or institutions.

[0078] The experiment was roughly divided into four stages: tree temperature rise, water evaporation, carbonization development, and open flame flashover. The phenomena in each stage are described below.

[0079] During the initial stage of tree temperature rise, visible light spots appear at the contact point, while other parts of the tree show no light. This is because the current passing through the contact point causes a localized temperature increase. As the current continues, the tree's temperature gradually rises, and heat from the contact point spreads to other parts of the tree. During this process, the tree's electrical conductivity gradually increases with temperature, but moisture evaporation or carbonization has not yet occurred. The temperature rise is most significant during this stage, and the rate of temperature rise may vary considerably between different trees.

[0080] During the evaporation stage, as the tree temperature rises further, moisture begins to evaporate. At this time, water vapor will appear to be spraying from the tree surface, indicating that the moisture inside the tree is evaporating to the outside. The evaporation process absorbs a large amount of heat, which helps to inhibit further temperature increases. As the tree's moisture gradually evaporates and its water content decreases, the tree's electrical conductivity changes. In this stage, moisture evaporation not only helps to slow down the temperature rise but also provides conditions for subsequent carbonization.

[0081] During the carbonization development stage, the carbonization process begins to manifest as the tree's temperature continues to rise. The carbonization path starts at the point of contact and gradually extends towards the ground, typically expanding vertically much faster than laterally. The width of the carbonization path is usually greatest at the point of contact and extends downwards over time. Furthermore, the expansion of the carbonization path is not always continuous; it may pause temporarily before carbonization resumes in previously uncarbonized areas. During this stage, the tree's electrical resistance gradually increases, and the carbonized areas exhibit bright spots of light, the positions of which vary randomly and over time.

[0082] During the open-flame flashover stage, as the charred path extends further and reaches a certain extent, the trees begin to produce open flames. These flames burn along the charred path and may spread to surrounding areas. At this point, a faint flash often appears at the end of the path, followed by blackening and continued elongation. In the final stages of the fault process, the charred path extends towards the ground, but does not produce a wire-to-ground flashover. As the flames expand, the trees bend and eventually form a ground fire.

[0083] As observed from the phenomena in the four stages described above, when TSF (Total Fractured Tree) reaches the carbonization development stage, carbonization has already begun, and the carbonization pathway of the tree gradually expands, at which point the fire risk begins to emerge. As carbonization progresses, the tree's structure is damaged, and the high temperatures generated by the electric current make the carbonization pathway increasingly prominent, gradually extending towards the trunk and the ground. With the expansion of the carbonization pathway, the decomposition of organic matter inside the tree generates a large amount of heat, increasing the potential fire risk.

[0084] If the carbonized area continues to expand, especially in the lower parts of trees and in drier environments, the flames can easily spread to the surrounding vegetation, creating conditions conducive to a forest fire. Particularly after carbonization reaches a certain depth, the fire can spread rapidly, endangering the surrounding ecosystem and safety. Therefore, from the third stage onwards, the danger of forest fires increases significantly. To estimate the timing of the fire, it is necessary to model the tree warming and moisture evaporation stages.

[0085] Step 3: Calculate the heat absorption of water evaporation in the tree model based on real-time data, then calculate the water evaporation mass based on the heat absorption of water evaporation, update the tree moisture content using the water evaporation mass, and save it in time alignment.

[0086] This step involves modeling the tree. When a wire touches the tree surface, current flows from the wire through each branch to the ground. To simplify the analysis, the tree is approximated as a cylinder with uniform electrical and thermal properties, and the transition zones between branches are ignored. For example... Figure 3 As shown, trees, as typical fractal structures, exhibit similar geometric features from the trunk to the branches and twigs. Therefore, a fractal network model can be used to simplify the tree morphology. By setting the interlayer length and radius ratio, and assuming that the electrical conductivity is related to temperature and water content, the electrical conductivity of each layer can be obtained based on the branching structure.

[0087] The electrical conductivity of trees is affected by temperature and moisture content; therefore, the core parameters of the model include the tree's temperature, moisture content, and size. The total resistance of the tree's superoxide dissipation (TSF) is equivalent to the total resistance of all branches along this current path. Current flowing through the tree generates Joule power, part of which is used to raise the wood temperature, part is dissipated through convection and radiation, and the remainder is lost to moisture evaporation.

[0088] Given the fault voltage and environmental parameters, the initial current and generated Joule power of the tree can be determined by calculating its initial resistance. Using this initial resistance, the convective and radiative heat dissipation power at the initial moment can be further calculated. Figure 4 As shown, as the iteration progresses, the Joule heat and water evaporation power at the current moment are used to update the changes in tree temperature and moisture content. These changes affect the electrical conductivity of the tree material, thereby affecting the resistance of each branch and the total fault resistance in the pathway.

[0089] Specifically, the formula for calculating the resistance in the resistance simulation curve is as follows:

[0090]

[0091] In the formula, n is the level of the line in the tree model, l0 is the length of the basic branch in the tree model, i.e. the height of the trunk, and r0 is the radius of the basic branch, i.e. the radius of the trunk.

[0092] The tree model is a fractal network model simplified from the morphology of experimental trees. In the tree model, α and β are defined as the ratio of the length of the branches in the (k+1)th layer network and the ratio of the radius of the branches in the kth layer network, respectively, as follows:

[0093]

[0094] In the formula, l k l k+1These are the branch lengths of the k-th layer network and the (k+1)-th layer network, respectively, r k r k+1 These are the tree radii of the k-th layer network and the tree radii of the (k+1)-th layer network, respectively.

[0095] The method for calculating the mass of water evaporated is as follows:

[0096] Calculate the total heat generated Q by the current passing through the tree at time t. s :

[0097]

[0098] In the formula, U is the phase voltage of the conductor connected to the tree; it should be noted that the heat generated by the current calculated in the above formula is Q. s To calculate the heat generation of a single branch in one level of the tree model, when considering the total heat generation of the entire tree model, it is necessary to calculate the heat generation of a single branch in each level separately, and then sum them up as the total heat generation of the entire tree model. Subsequent calculations of convective heat dissipation, radiative heat dissipation, water evaporation heat absorption, and tree temperature rise heat absorption all represent heat generated in a single level of the tree model, and the heat dissipation or absorption of each level must be summed up as the total heat dissipation or absorption of the entire tree model.

[0099] When an electric current passes through a tree, the Joule heat (i.e., the heat generated by the current) is consumed in three ways inside the tree: part of the heat is used to raise the temperature of the wet wood itself, part of it is transferred to the external environment through convection and radiation on the surface of the wood, and the remaining part is absorbed by the water and becomes the latent heat of vaporization of the water, which is used for the phase change of water from liquid to gas.

[0100] The heat dissipation and absorption of trees include convective heat dissipation, radiative heat dissipation, heat absorption due to temperature rise, and heat absorption due to water evaporation. The total heat output, after deducting convective and radiative heat dissipation, represents the total heat absorption. The product of the total heat absorption and the evaporation absorption ratio is the heat absorption due to water evaporation, expressed as follows:

[0101] Q w =(Q s -Q c -Q r )·k f

[0102] Q c =∫k c S c (TT e )dt

[0103]

[0104] k f = (1+e) 98-T )-1

[0105] In the formula, Q w As water evaporates and absorbs heat, Q s Q represents the total heat production. c For convective heat dissipation, Q r k represents the heat dissipation due to radiation. c S is the heat dissipation coefficient of tree branches. c T is the lateral surface area of ​​the tree branch, and T is the temperature of the tree. e For ambient temperature, k r δ0 is the dendritic radiative heat transfer coefficient, δ0 is the Stefan-Boltzmann constant, and k is the dendritic radiative heat transfer coefficient. f This is the evaporation absorption ratio coefficient.

[0106] Calculate the mass of water evaporated based on the heat absorbed during water evaporation:

[0107]

[0108] In the formula, Δm is the mass of water evaporated, and T w The temperature of the water.

[0109] The water content of the new trees then becomes W-ΔW, where:

[0110]

[0111] The ratio of the water evaporation mass obtained by the above formula to the absolute dry mass of the wood block obtained by the experiment is used as the change in the moisture content of the tree.

[0112] The water evaporation mass and moisture content change calculated in this step are also the values ​​of a single branch in one level of the tree model. When considering the water evaporation mass and moisture content change of the entire tree model, it is necessary to calculate a single branch in each level and summarize the water evaporation mass and moisture content change of each level as the entire tree model.

[0113] Step four: Based on real-time data, aligned tree moisture content, and voltage and current data collected in the experimental environment, fit the relationship between tree conductivity, moisture content, and temperature throughout the entire process to obtain the conductivity function.

[0114] The relationship between electrical conductivity, moisture content, and temperature of trees throughout the entire process was fitted using the least squares method. The fitted relationship between electrical conductivity and temperature and moisture content is expressed as follows:

[0115] lnσ t (W,T)=7.458W+0.057T-0.050W·T-10.754

[0116] In the formula, σ t(W,T) represents the electrical conductivity calculated at time t relative to temperature and moisture content, where W is the moisture content of the tree and T is the temperature of the tree.

[0117] Step 5: Using the conductivity function, construct a simulated resistance curve based on the tree's moisture content and temperature, and construct a measured resistance curve using voltage and current data collected in the experimental environment.

[0118] Step six: Compare the simulated resistance curve and the measured resistance curve. The moment when the simulated resistance curve and the measured resistance curve show a clear divergence is the moment when an open flame appears.

[0119] The methods for determining obvious bifurcation include the difference index determination method and the visualization analysis method;

[0120] The difference index is a relative index, and its calculation method is as follows:

[0121]

[0122] In the formula, Δy t Let y1(t) be the resistance value corresponding to the simulated resistance curve at time t, and y2(t) be the resistance value corresponding to the measured resistance curve at time t. ∈ is a preset parameter used to avoid the denominator being zero; when Δy t When the preset threshold is exceeded, it is determined that the simulated resistance curve and the measured resistance curve show a clear divergence.

[0123] Visual analysis maps simulated resistance curves and measured resistance curves to the same coordinate system, outputting coordinate system images in real time for manual intervention and judgment. Figure 5 , 6 As shown, after manual intervention, when the resistance curve develops to the corresponding time in the circled part of the coordinate system, it is easy to determine that the simulated resistance curve and the measured resistance curve show obvious bifurcation.

[0124] In other embodiments of the present invention, the method for determining obvious bifurcation also employs statistical analysis, statistical detection, and time point location methods.

[0125] Statistical analysis methods are used to analyze changes in difference indicators to determine the timing and significance of bifurcation. For example, the moving average or variance of the difference indicator is calculated, and it is determined whether it has increased significantly. A threshold is set (such as k times the previous difference mean). When the difference indicator first exceeds the threshold, it is considered that a bifurcation has occurred.

[0126] Statistical detection methods use statistical methods to determine whether the bifurcation is significant. The time series is divided into an early stage (with a better fit) and a later stage, and the mean of the difference index is calculated for each stage. The difference between the early and late stages is compared using a t-test to determine whether the difference is significant. Alternatively, the sequence variation detection (CUSUM) method can be used to identify the points of change in the mean or distribution of the time series.

[0127] The time-point localization method uses dynamic programming methods (such as Pruned Exact Linear Time, PELT) to find the globally optimal change point, or uses Bayesian Change Point Detection to obtain the change point.

[0128] This embodiment also includes two sets of verification experiments. Verification Experiment 1 has the following preset values: trunk height 1.52m, trunk radius 0.051m, initial moisture content 0.941%, initial temperature 31.9℃, specific heat capacity of the tree 1408 J / kg*K, tree density 705 kg / m³, and specific heat capacity of water 4200 J / kg*K. Comparison with actual whole-tree test data yields the following results: Figure 5 The effect shown. In Figure 5 In the coordinate system, the blue line represents the measured resistance curve, whose resistance value is calculated from the voltage and current data collected by the voltage and current sensors; the orange line represents the simulated resistance curve, whose resistance value is R calculated using the above formula. t The time corresponding to the real-world scene on the right side of the image is circled in the coordinate system.

[0129] The preset values ​​for verification experiment two are: a tree trunk height of 2.05m, a trunk radius of 0.032m, an initial moisture content of 0.713%, an initial temperature of 35.1℃, a specific heat capacity of 1495 J / kg*K, a tree density of 1050 kg / m³, and a specific heat capacity of 4200 J / kg*K. These values ​​are then compared with actual whole-tree experimental data to obtain the following results. Figure 6 The effect shown. In Figure 6 In the coordinate system, the blue line represents the measured resistance curve, whose resistance value is calculated from the voltage and current data collected by the voltage and current sensors; the orange line represents the simulated resistance curve, whose resistance value is R calculated using the above formula. t The time corresponding to the real-world scene on the right side of the image is circled in the coordinate system.

[0130] from Figure 5 , 6 As can be seen from this embodiment, the method described can be applied to accurately estimate the time of fire ignition, effectively identify the time of fire occurrence, help analyze the source of failure and ignition mechanism, clarify fire responsibility, and provide a scientific basis for subsequent fire prevention measures and equipment protection strategies.

[0131] Example 2

[0132] This embodiment is a system for determining the timing of a fire caused by a tree contact fault in an overhead power distribution conductor. The system is used to implement the determination method described in Embodiment 1, including:

[0133] The experimental environment module is used to simulate the entire process of a power distribution overhead conductor touching a tree fault, including a neutral point ungrounded simulation section and a conductor touching a tree simulation section.

[0134] The parameter acquisition module further includes: a voltage and current acquisition unit for acquiring phase voltage and grounding current data in the experimental environment in a time-aligned manner; and a temperature acquisition unit for acquiring the temperature of trees during the experiment and saving it in a time-aligned manner.

[0135] The data processing module further includes: a water evaporation calculation unit, used to calculate the heat absorbed by water evaporation of the tree model based on real-time collected data, and thereby calculate the water evaporation mass, used to update the real-time water content of the tree; and an electrical conductivity fitting unit, used to fit the relationship between the tree's electrical conductivity, water content and temperature based on experimental data, and generate an electrical conductivity function.

[0136] The resistance curve generation module further includes: a resistance simulation curve construction unit, used to construct a resistance simulation curve based on the conductivity function and the water content and temperature of the tree; and a resistance measurement curve construction unit, used to construct a resistance measurement curve based on voltage and current data collected in the experimental environment.

[0137] The determination module is used to compare the simulated resistance curve with the measured resistance curve and determine the moment when the simulated resistance curve and the measured resistance curve clearly diverge as the moment when an open flame appears.

[0138] The above description is only a preferred embodiment of the present invention. It should be noted that those skilled in the art can make several modifications and improvements without departing from the inventive concept of the present invention, and these all fall within the protection scope of the present invention.

Claims

1. A method for determining the timing of a fire caused by a tree contact fault in an overhead power distribution conductor, characterized in that... Includes the following steps: An experimental environment was set up to simulate the entire process of a power distribution overhead conductor touching a tree, and data of the entire process was collected in the experimental environment at a preset sampling frequency. The initial moisture content of the experimental trees was obtained, and the complete process data was continuously collected and analyzed over time during the experiment to generate real-time data. The heat absorbed by water evaporation in the tree model is calculated based on real-time data. Then, the mass of water evaporation is calculated based on the heat absorbed by water evaporation. The water evaporation mass is used to update the tree moisture content and is saved in time alignment. Based on real-time data, aligned tree moisture content, and voltage and current data collected in the experimental environment, the relationship between tree conductivity, moisture content, and temperature throughout the entire process is fitted to obtain the conductivity function. The conductivity function is used to construct a simulated resistance curve based on the tree's water content and temperature, while the voltage and current data collected in the experimental environment are used to construct a measured resistance curve. The simulated resistance curve and the measured resistance curve are compared. The moment when the simulated resistance curve and the measured resistance curve show a clear bifurcation is determined as the moment when an open flame appears. The method for determining the clear bifurcation is the difference index determination method. The difference index is a relative index, and the calculation method is as follows: In the formula, for Difference indicators over time for The resistance value corresponding to the resistance simulation curve at any given time. for The resistance value corresponding to the measured resistance curve at any given time. These are preset parameters used to avoid a denominator of zero; when When the preset threshold is exceeded, it is determined that the simulated resistance curve and the measured resistance curve show a clear divergence.

2. The method for determining the ignition time of a tree-touching fault in an overhead power distribution conductor according to claim 1, characterized in that, The experimental environment includes a neutral point ungrounded simulation section, a conductor-to-tree simulation section, and a data acquisition section. The neutral point ungrounded simulation section consists of a three-phase overhead conductor that is energized. The conductor-to-tree simulation section includes trees transplanted to the test site, with one phase drawn from the three-phase overhead conductor and connected to the tree. The data acquisition section continuously records the phase voltage and grounding current throughout the entire process, records the experimental phenomena during the ignition process, and records the temperature changes of the tree until the discharge channel penetrates the vegetation and causes a short circuit.

3. The method for determining the ignition time of a tree-touching fault in an overhead power distribution conductor according to claim 1, characterized in that, The complete process data includes conductor phase voltage, current passing through the experimental tree, and temperature of the experimental tree.

4. The method for determining the ignition time of a tree-touching fault in an overhead power distribution conductor according to claim 1, characterized in that, The method for obtaining the initial moisture content includes experimental weighing and preset values; The formula for calculating the experimental weight is: In the formula, The fresh weight of the wood blocks obtained from the experimental sampling. The dry weight of the wood block; The preset values ​​are derived from existing data on the corresponding tree species in the experimental field during the experimental season.

5. The method for determining the ignition time of a tree-touching fault in an overhead power distribution conductor according to claim 1, characterized in that, The experimental process includes, in sequence, the tree temperature rise stage, the water evaporation stage, the carbonization development stage, and the open flame flashover stage.

6. The method for determining the ignition time of a tree-touching fault in an overhead power distribution conductor according to claim 1, characterized in that, The relationship between electrical conductivity, moisture content, and temperature of trees throughout the entire process was fitted using the least squares method. The fitted relationship between electrical conductivity and temperature and moisture content is expressed as follows: In the formula, for The conductivity calculated relative to temperature and moisture content at a given time. For the moisture content of trees, The temperature of the tree.

7. The method for determining the ignition time of a tree-touching fault in an overhead power distribution conductor according to claim 6, characterized in that, The formula for calculating the resistance in the resistance simulation curve is as follows: In the formula, This refers to the hierarchy of the lines in the tree model. The basic branch length in the tree model, i.e., the trunk height. The radius of the basic branches is the same as the radius of the trunk. The tree model is a fractal network model simplified from the morphology of experimental trees. In this tree model, the following is defined: The first Layer network branches and the first The ratio of tree lengths to tree radii in a layered network is expressed as follows: In the formula, They are the first Tree length and the first layer of the network The length of the branches in the layered network. They are the first The tree radius of the layer network and the first The tree radius of the layer network.

8. The method for determining the ignition time of a tree-touching fault in an overhead power distribution conductor according to claim 7, characterized in that, The method for calculating the mass of water evaporated is as follows: calculate The total heat generated when current passes through a tree at any given moment : In the formula, This refers to the phase voltage of the conductor connected to the tree. The heat dissipation and absorption of trees include convective heat dissipation, radiative heat dissipation, heat absorption due to temperature rise, and heat absorption due to water evaporation. The total heat output, after deducting convective and radiative heat dissipation, represents the total heat absorption. The product of the total heat absorption and the evaporation absorption ratio is the heat absorption due to water evaporation, expressed as follows: In the formula, The evaporation of water absorbs heat. For total heat production, For convective heat dissipation, For radiative heat dissipation, This is the evaporation absorption ratio coefficient. For tree temperature; Calculate the mass of water evaporated based on the heat absorbed during water evaporation: In the formula, The mass of water evaporated. The temperature of the water.

9. A system for determining the timing of a fire caused by a tree contact fault in an overhead power distribution conductor, characterized in that, The system is used to implement the determination method as described in any one of claims 1-8, including: The experimental environment module is used to simulate the entire process of a power distribution overhead conductor touching a tree fault, including a neutral point ungrounded simulation section and a conductor touching a tree simulation section. The parameter acquisition module further includes: a voltage and current acquisition unit for acquiring phase voltage and grounding current data in the experimental environment in a time-aligned manner; and a temperature acquisition unit for acquiring the temperature of trees during the experiment and saving it in a time-aligned manner. The data processing module further includes: a water evaporation calculation unit, used to calculate the heat absorbed by water evaporation of the tree model based on real-time collected data, and thereby calculate the water evaporation mass, used to update the real-time water content of the tree; and an electrical conductivity fitting unit, used to fit the relationship between the tree's electrical conductivity, water content and temperature based on experimental data, and generate an electrical conductivity function. The resistance curve generation module further includes: a resistance simulation curve construction unit, used to construct a resistance simulation curve based on the conductivity function and the water content and temperature of the tree; and a resistance measurement curve construction unit, used to construct a resistance measurement curve based on voltage and current data collected in the experimental environment. The determination module is used to compare the simulated resistance curve with the measured resistance curve and determine the moment when the simulated resistance curve and the measured resistance curve clearly diverge as the moment when an open flame appears.

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