Long-distance laser deicing method suitable for power transmission line in alpine region

Abstract

The application relates to the technical field of power transmission line maintenance, in particular to a long-distance laser deicing method for power transmission lines in high-cold regions. The method comprises the following steps: clustering target thermal response coefficients to obtain a target cluster; analyzing the change rate of the thermal response coefficients of multiple adjacent targets in the target interval, the maximum value of the target thermal response coefficient and the dispersion of the target thermal response coefficient to determine an environmental influence coefficient; calculating a first predicted power based on the relative deviation of the transmission power at each sampling time in the current interval and the average power in the current interval and the distance between each sampling time and the target time; calculating a second predicted power based on the influence weight of each subinterval in the historical interval and the corresponding historical average power; obtaining the target power at the target time according to the first predicted power, the second predicted power and the environmental influence coefficient, and controlling the deicing equipment to operate at the target power. The application can significantly improve the safety and efficiency of deicing operations.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power transmission line maintenance, in particular to a long-distance laser deicing method for power transmission lines in high-cold regions. BACKGROUND

[0002] The current line deicing is through applying large current to melt ice. The deicing of other components is mainly by artificial ice shedding, which is low in efficiency and poor in safety.

[0003] As a new type of ice melting method with non-contact, long-distance, high energy and live working characteristics, laser deicing is very suitable for deicing the insulators and switch blades on the line and other important key equipment without interrupting power supply. It uses high-energy laser beam to irradiate the ice layer in a non-contact manner, and the ice layer absorbs energy locally and instantaneously to melt or evaporate through photothermal effect, so as to realize precise and remote cleaning of the power transmission line.

[0004] The essence of laser deicing is to use photothermal effect, but the absorption and reaction of laser energy by the wire and ice layer are different. The ideal situation is that the laser is only absorbed by the ice layer, and the wire (usually aluminum or steel core) below is not absorbed at all. However, in reality, the metal wire also absorbs part of the laser energy and generates heat. If the laser power or irradiation time is not properly controlled, it may cause the temperature of the wire to be too high, thereby damaging its mechanical strength and electrical conductivity, and even causing annealing effect (causing the metal to soften). SUMMARY

[0005] In order to solve the above technical problems, the purpose of the present application is to provide a long-distance laser deicing method for power transmission lines in high-cold regions, and the technical solution adopted is as follows:

[0006] In the first aspect, a long-distance laser deicing method for power transmission lines in high-cold regions is provided, and the method comprises:

[0007] Clustering a plurality of target thermal response coefficients to obtain a target cluster; the target thermal response coefficient is obtained by screening the thermal response coefficient in the current interval, and the thermal response coefficient indicates the ratio of the transmission power of the deicing device to the temperature of the cable;

[0008] Analyzing the change rate of a plurality of adjacent target thermal response coefficients in the target interval, the extreme value of the target thermal response coefficient in the target interval, and the dispersion of the target thermal response coefficient in the target interval to determine an environmental influence coefficient; the target interval is determined according to the interval covered by the sampling time of each target thermal response coefficient in the target cluster;

[0009] Based on the relative deviation of the transmission power at each sampling time in the current interval from the average power in the current interval and the distance between each sampling time and the target time, a first predicted power at the target time is calculated.

[0010] calculate a second predicted power at the target moment based on an influence weight of each sub-interval in the historical interval and a corresponding historical average power; each sub-interval indicates a time interval covered by each cluster of the clustered historical target thermal response coefficients, the historical target thermal response coefficients are obtained by screening the thermal response coefficients in the historical interval, and the influence weight of each sub-interval is determined according to the similarity between the historical target thermal response coefficients of the sub-interval and the thermal response coefficients of the target interval;

[0011] correct the current transmission power according to the first predicted power, the second predicted power and the environmental influence coefficient, to obtain a target power at the target moment, and control the deicing device to operate at the target power.

[0012] Optionally, before the clustering of the plurality of target thermal response coefficients to obtain the target cluster, the method further comprises:

[0013] at each sampling moment of the current interval, the temperature of the cable and the transmission power of the deicing device are obtained, and the ratio of the transmission power of the deicing device to the temperature of the cable is calculated to obtain a thermal response coefficient at each sampling moment; the current interval includes the current moment and a plurality of sampling moments before the current moment;

[0014] calculate the mean value of the plurality of thermal response coefficients in the current interval to obtain a thermal response mean value;

[0015] calculate the difference between each thermal response coefficient in the current interval and the thermal response mean value to obtain a thermal response difference value of the thermal response coefficient;

[0016] screen the plurality of thermal response difference values in the current interval according to the box plot algorithm, and determine the thermal response coefficient corresponding to the thermal response difference value less than the quartile as the target thermal response coefficient.

[0017] Optionally, the clustering of the plurality of target thermal response coefficients to obtain the target cluster comprises:

[0018] perform hierarchical clustering on the plurality of target thermal response coefficients in the current interval to obtain a plurality of clusters;

[0019] determine the cluster with the largest number of target thermal response coefficients as the target cluster.

[0020] Optionally, the analysis of the change rate of the plurality of adjacent target thermal response coefficients in the target interval, the extreme value of the target thermal response coefficient in the target interval, and the dispersion of the target thermal response coefficient in the target interval to determine the environmental influence coefficient comprises:

[0021] calculate the ratio of the number of all thermal response coefficients in the target interval to the number of target thermal response coefficients in the target interval to obtain the proportion of target thermal response coefficients in the target interval;

[0022] The product of the variance of all target thermal response coefficients in the target interval and the proportion of the target thermal response coefficients in the target interval is calculated to obtain a coefficient of variation of the target interval; the coefficient of variation of the target interval indicates the fluctuation degree of the target thermal response coefficients in the target interval; the dispersion degree of the target thermal response coefficients in the target interval includes the coefficient of variation of the target interval;

[0023] A coordinate system is established with each sampling time in the target interval as the horizontal axis and the thermal response coefficient at the sampling time as the vertical axis, the absolute value of the slope between each adjacent target thermal response coefficient is calculated to obtain the change rate of each adjacent target thermal response coefficient;

[0024] The mean value of the change rates of the plurality of adjacent target thermal response coefficients in the target interval, the coefficient of variation of the target interval, and the extreme value of the target thermal response coefficients in the target interval are analyzed to determine an environmental influence coefficient; the environmental influence coefficient indicates the influence degree of the environment on the deicing of the deicing equipment.

[0025] Optionally, the analyzing the mean value of the change rates of the plurality of adjacent target thermal response coefficients in the target interval, the coefficient of variation of the target interval, and the extreme value of the target thermal response coefficients in the target interval to determine the environmental influence coefficient comprises:

[0026] The difference between the maximum target thermal response coefficient and the minimum target thermal response coefficient in the target interval is calculated to obtain a range of the target interval;

[0027] The mean value of the change rates of the plurality of adjacent target thermal response coefficients in the target interval, the coefficient of variation of the target interval, and the range of the target interval are multiplied to obtain an initial environmental influence coefficient;

[0028] The initial environmental influence coefficient is normalized to obtain the environmental influence coefficient.

[0029] Optionally, the normalizing the initial environmental influence coefficient to obtain the environmental influence coefficient comprises:

[0030] The initial environmental influence coefficient is normalized by using a linear normalization function to obtain the environmental influence coefficient.

[0031] Optionally, the calculating the first predicted power at the target time based on the relative deviation degree of the transmission power at each sampling time in the current interval from the average power in the current interval and the distance between each sampling time and the target time comprises:

[0032] The ratio of the transmission power at each sampling time in the current interval to the average power in the current interval is calculated to obtain the relative deviation degree of the sampling time;

[0033] The distance between each sampling time in the current interval and the target time is calculated to obtain the interval distance of the sampling time.

[0034] calculate the product of the relative deviation degree of each sampling time and the reciprocal of the interval distance of the sampling time, to obtain the prediction weight of the sampling time;

[0035] calculate the product of the prediction weight of each sampling time in the current interval and the transmission power of the sampling time, to obtain the prediction power corresponding to the sampling time;

[0036] calculate the mean of the prediction power of the plurality of sampling times in the current interval, to obtain the first prediction power of the target time.

[0037] Optionally, the second prediction power of the target time is calculated based on the influence weight of each sub-interval in the historical interval and the corresponding historical average power, comprising:

[0038] According to the box plot algorithm, the plurality of historical thermal response coefficients in the historical interval are screened, and the historical thermal response coefficients less than the quartile are determined as the historical target thermal response coefficients;

[0039] The plurality of historical target thermal response coefficients in the historical interval are clustered to obtain a plurality of historical clusters, and the time interval covered by the historical target thermal response coefficients in each cluster is determined as the sub-interval corresponding to the cluster;

[0040] For each sub-interval, the ratio of the number of all historical thermal response coefficients in the sub-interval to the number of historical target thermal response coefficients in the sub-interval is calculated to obtain the proportion of historical target thermal response coefficients in the sub-interval;

[0041] The product of the variance of all historical target thermal response coefficients in the sub-interval and the proportion of historical target thermal response coefficients in the sub-interval is calculated to obtain the coefficient of variation of the sub-interval; the coefficient of variation of the sub-interval indicates the fluctuation degree of the historical target thermal response coefficients in the sub-interval;

[0042] The historical target thermal response coefficients of each sub-interval form a sequence to obtain the historical target thermal response coefficient sequence of the sub-interval, and the target thermal response coefficients of the target interval form a sequence to obtain the target thermal response coefficient sequence of the target interval;

[0043] The DTW value of the historical target thermal response coefficient sequence of each sub-interval and the target thermal response coefficient sequence of the target interval is calculated to obtain the similarity between the sub-interval and the target interval;

[0044] The distance between the center time of each sub-interval and the center time of the target interval is calculated to obtain the interval distance of the sub-interval;

[0045] The influence weight of each sub-interval is determined according to the reciprocal of the cumulative product of the coefficient of variation of each sub-interval, the similarity between the sub-interval and the target interval, and the interval distance of the sub-interval.

[0046] The second predicted power at the target time is calculated based on the influence weight of each sub-interval in the historical interval and the corresponding historical average power.

[0047] Optionally, the second predicted power at the target time is calculated based on the influence weight of each sub-interval in the historical interval and the corresponding historical average power, comprising:

[0048] The product of the influence weight of each sub-interval and the historical average power of the sub-interval is calculated to obtain the predicted power of the sub-interval.

[0049] The mean of the predicted powers of the multiple sub-intervals in the historical interval is calculated to obtain the second predicted power at the target time.

[0050] Optionally, the current transmitting power is corrected according to the first predicted power, the second predicted power and the environmental influence coefficient to obtain the target power at the target time, and the de-icing equipment is controlled to operate at the target power, comprising:

[0051] The mean of the first predicted power and the second predicted power is calculated to obtain the predicted power at the target time.

[0052] The difference between the predicted power at the target time and the current transmitting power is calculated to obtain a power difference.

[0053] The product of the power difference and the environmental influence coefficient is calculated to obtain a correction coefficient.

[0054] The mean of the transmitting powers corresponding to the multiple target thermal response coefficients of the current interval is calculated to obtain the current transmitting power.

[0055] The sum of the correction coefficient and the predicted power at the target time is calculated to obtain the target power at the target time, and the de-icing equipment is controlled to operate at the target power.

[0056] On the basis of conforming to the common sense in the art, the above-mentioned preferred conditions can be combined arbitrarily, i.e. the preferred examples of the present application are obtained.

[0057] The application has the following beneficial effects: the target heat response coefficient is dynamically screened and clustered to accurately define a target interval representing a stable working condition, and a precise quantitative environmental influence coefficient is comprehensively determined based on the change rate, maximum value and dispersion of the heat response coefficient in the target interval, so as to realize adaptive perception of environmental interference. By fusing local trend prediction based on the current interval power relative deviation and time distance and global experience prediction based on historical interval similarity weighted matching, and introducing the environmental influence coefficient for collaborative correction, the target power capable of responding to real-time working condition changes and historical experience rules is finally generated. The contradiction between deicing efficiency and cable safety caused by uneven ice distribution and environmental fluctuations during laser deicing in high-cold environments is effectively overcome, and the ice on the power transmission line is quickly, adaptively and accurately removed without damaging the cable, thereby significantly improving the safety, efficiency and intelligent level of deicing operation. BRIEF DESCRIPTION OF DRAWINGS

[0058] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0059] Figure 1 A flowchart of a power transmission line long-distance laser deicing method suitable for high-cold regions in an embodiment;

[0060] Figure 2 A structural schematic diagram of a power transmission line long-distance laser deicing system suitable for high-cold regions in an embodiment;

[0061] Figure 3 A structural schematic diagram of an electronic device in an embodiment. DETAILED DESCRIPTION

[0062] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined invention purposes, the following describes the specific implementation, structure, features and effects of a power transmission line long-distance laser deicing method suitable for high-cold regions according to the present application in combination with the drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0063] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs.

[0064] A specific scheme of a long-distance laser deicing method for power transmission lines in high-cold regions is specifically described below with reference to the drawings. As shown in Figure 1 The method comprises the following steps:

[0065] S11, clustering a plurality of target thermal response coefficients to obtain a target cluster.

[0066] The target thermal response coefficient is obtained by screening the thermal response coefficient in the current interval. The thermal response coefficient indicates the ratio of the transmission power of the deicing device to the temperature of the cable, represents the power input level corresponding to unit temperature change, and is used to quantify the thermal efficiency and stability of the current deicing condition.

[0067] The current interval includes the current time and a plurality of sampling times before the current time.

[0068] The deicing device can be any device with laser transmission function, and the power of the laser output can reach the minimum power requirement of laser deicing.

[0069] In the present application, the temperature of the cable during the laser deicing process is obtained in real time by an infrared thermal imager, and then the power of the laser transmitter is adjusted in real time according to the temperature, so as to avoid damaging the cable due to excessive power.

[0070] The basic principle of infrared temperature measurement method is that any object with a temperature higher than absolute zero will radiate infrared rays, and the radiation energy of the object has a certain functional relationship with the surface temperature of the object (following the Stefan-Boltzmann law). By measuring the radiation energy of the object in a specific infrared band, the surface temperature of the object can be calculated.

[0071] The infrared thermal imager is equivalent to an infrared camera, which can generate a temperature distribution image (thermal image) of the entire scene. Each pixel in the image corresponds to a temperature value. The infrared thermal imager shoots a thermal image containing the entire laser action area (laser spot and nearby wires), and through image processing algorithms, the highest temperature, average temperature of the laser spot area, and the temperature of other key points (such as adjacent non-irradiated areas) of the wires can be identified and extracted in real time.

[0072] The infrared radiation emitted by the surface of the cable due to temperature is received and focused by the optical lens system of the infrared temperature measuring instrument or the infrared thermal imager. The focused infrared rays are guided to the infrared detector (such as tellurium cadmium mercury, vanadium oxide focal plane array, etc.). The detector converts the invisible infrared light signal into a weak electrical signal. The performance of the detector directly determines the accuracy, speed and sensitivity of temperature measurement.

[0073] The DSP (Digital Signal Processor) calculates the final cable surface temperature value according to the converted electrical signal, combines the set emissivity and environmental parameters, and uses the built-in algorithm model.

[0074] The collected temperature data is sent to the control center (such as PLC (Programmable Logic Controller) or industrial computer) in real time.

[0075] Information can be transmitted through RS-485 (commonly using Modbus RTU protocol), Ethernet (Modbus TCP / IP, Profinet, EtherCAT, etc.), digital transmission can carry more information (such as device status, diagnostic data), high speed, and good anti-interference ability. On the deicing robot or vehicle platform, industrial bus or industrial Ethernet is usually used to connect each sensor (temperature measuring instrument, thermal imager, visible light camera) to the main controller to ensure real-time and reliability.

[0076] Stored data is not only used for real-time control, but also for post-analysis, fault diagnosis and system optimization. Each data record usually contains: time stamp accurate to milliseconds, temperature from one or more measuring points of the temperature measuring instrument, or average or maximum temperature of the area of interest defined by the thermal imager, laser output power at the moment, laser spot position, environmental temperature and humidity, device GPS (Global Positioning System) position, etc.

[0077] In severe cold and snowy weather, the icing of the line will dramatically increase the weight of the conductor, causing line dancing, hardware damage, and even tower collapse and broken lines, leading to large-scale power outages and causing huge losses to the economy and society. Traditional deicing methods such as manual knocking are inefficient and dangerous, and direct current short circuit melting method requires power outage operation and high energy consumption.

[0078] Laser deicing is a cutting-edge solution to this challenge, with the core advantage of non-contact, precision, efficiency and easy automation. It uses high-energy laser beams to irradiate ice layers from a distance, and through photothermal effect, the ice body absorbs energy locally and instantaneously, causing melting or sublimation. The entire process does not require personnel to climb and risk, nor does it require power outage of the line, maximizing the continuity of power supply and the safety of operation and maintenance personnel.

[0079] Because the essence of deicing is photothermal conversion, in the ideal state, laser energy should only be absorbed by the ice layer. However, in reality, the underlying metal conductor (such as aluminum, steel) will also absorb part of the energy and heat up. If the power is too high or the irradiation time is too long, it may cause the conductor temperature to exceed the safety threshold, damaging its mechanical strength and electrical conductivity, and even causing metal annealing softening, which may cause irreversible damage to the line.

[0080] Therefore, intelligent and adaptive control of laser power is needed to ensure efficient removal of ice layers while ensuring the safety of the power transmission line.

[0081] In one embodiment, before clustering the plurality of target thermal response coefficients to obtain a target cluster, further comprising:

[0082] At each sampling time of the current interval, the temperature of the cable and the emission power of the deicing device are obtained, and the ratio of the emission power of the deicing device to the temperature of the cable is calculated to obtain a thermal response coefficient at each sampling time; the current interval includes the current time and a plurality of sampling times before the current time;

[0083] The mean value of the plurality of thermal response coefficients of the current interval is calculated to obtain a thermal response mean value;

[0084] The difference between each thermal response coefficient of the current interval and the thermal response mean value is calculated to obtain a thermal response difference value of the thermal response coefficient;

[0085] According to the box plot algorithm, the plurality of thermal response difference values of the current interval are screened, and the thermal response coefficient corresponding to the thermal response difference value less than the quartile is determined as the target thermal response coefficient.

[0086] At each sampling time of the current interval, the temperature of the cable and the emission power of the deicing device (laser deicing device) are obtained, and the ratio of the temperature of the cable at the i-th sampling time to the emission power of the deicing device is calculated to obtain a thermal response coefficient at the i-th sampling time .

[0087] Because in the process of deicing, the thickness of snow, the short distance between the emitter and the cable, etc. will affect the effect of the initial snow, and under the fixed laser emission power, the snow removal degree at different positions is not the same, so the temperature on the surface of the cable is also not the same, so the mean value of all thermal response coefficients of the current interval is calculated to obtain a thermal response mean value , and the difference between each thermal response coefficient of the current interval and the thermal response mean value is calculated to obtain a thermal response difference value of the thermal response coefficient .

[0088] According to the box plot algorithm, the plurality of thermal response difference values of the current interval are screened, and the thermal response coefficient corresponding to the thermal response difference value less than the quartile is determined as the target thermal response coefficient, the mean value of the laser emission power corresponding to the plurality of target thermal response coefficients of the current interval is calculated, and it is taken as the current emission power , wherein the box plot algorithm is a known technology, and will not be described here.

[0089] Because the coverage degree of ice and snow at the same position of the cable is approximately the same, and at different positions, the coverage of surface ice and snow will appear differences due to different wind speeds and different bending degrees of the cable, so it is necessary to adjust the target power according to the real-time snow removal situation.

[0090] Therefore, in one embodiment, the plurality of target thermal response coefficients are clustered to obtain a target cluster, comprising:

[0091] hierarchical clustering the plurality of target thermal response coefficients in the current interval to obtain a plurality of clusters;

[0092] determining the cluster with the largest number of target thermal response coefficients as the target cluster.

[0093] hierarchical clustering the plurality of target thermal response coefficients in the current interval, taking each target thermal response coefficient as a one-dimensional data point, calculating the Euclidean distance between each pair of target thermal response coefficients based on their numerical values and constructing a distance matrix, using a bottom-up agglomerative hierarchical clustering method, initially each target thermal response coefficient is an independent cluster, then iteratively merging the two clusters with the closest distance according to a single connection, full connection or average connection strategy, and stopping clustering when the number of clusters reaches a preset threshold or the distance between the two clusters after the last merging exceeds a preset distance threshold, finally obtaining a plurality of clusters, each cluster containing target thermal response coefficients with similar values, representing stable sub-working conditions with similar thermal response characteristics in the current interval. In this application, the number of clustering layers is set to 2, i.e. two clusters are obtained, and the hierarchical clustering algorithm is prior art, which will not be described here.

[0094] determining the cluster with the largest number of target thermal response coefficients as the target cluster, determining the interval covered by the sampling time of each target thermal response coefficient in the target cluster as the target interval, and then analyzing the change of the target thermal response coefficient in the target interval to determine the influence coefficient of the environment on laser deicing under the current environment.

[0095] S12, analyzing the change rate of the plurality of adjacent target thermal response coefficients in the target interval, the maximum value of the target thermal response coefficient in the target interval, and the dispersion of the target thermal response coefficient in the target interval to determine the environmental influence coefficient.

[0096] wherein the target interval is determined according to the interval covered by the sampling time of each target thermal response coefficient in the target cluster.

[0097] The environmental influence coefficient represents the degree of influence of the environment on laser deicing.

[0098] In one embodiment, the change rate of the plurality of adjacent target thermal response coefficients in the target interval, the maximum value of the target thermal response coefficient in the target interval, and the dispersion of the target thermal response coefficient in the target interval are analyzed to determine the environmental influence coefficient, comprising:

[0099] calculating the ratio of the number of all thermal response coefficients in the target interval to the number of target thermal response coefficients in the target interval to obtain the proportion of target thermal response coefficients in the target interval;

[0100] The product of the variance of all target thermal response coefficients in the target interval and the proportion of the target thermal response coefficients in the target interval is calculated to obtain a coefficient of variation of the target interval; the coefficient of variation of the target interval indicates the fluctuation degree of the target thermal response coefficients in the target interval; the dispersion degree of the target thermal response coefficients in the target interval includes the coefficient of variation of the target interval;

[0101] A coordinate system is established with each sampling time in the target interval as the horizontal axis and the thermal response coefficient at the sampling time as the vertical axis, and the absolute value of the slope between each adjacent target thermal response coefficient is calculated to obtain the change rate of each adjacent target thermal response coefficient;

[0102] The mean value of the change rates of the plurality of adjacent target thermal response coefficients in the target interval, the coefficient of variation of the target interval, and the extreme value of the target thermal response coefficients in the target interval are analyzed to determine an environmental influence coefficient; the environmental influence coefficient indicates the influence degree of the environment on the deicing of the deicing equipment.

[0103] Specifically, the mean value of the change rates of the plurality of adjacent thermal response coefficients in the target interval, the coefficient of variation of the target interval, and the extreme value of the target thermal response coefficients in the target interval are analyzed to determine an environmental influence coefficient, including:

[0104] The difference between the maximum target thermal response coefficient and the minimum target thermal response coefficient in the target interval is calculated to obtain a range of the target interval;

[0105] The mean value of the change rates of the plurality of adjacent target thermal response coefficients in the target interval, the coefficient of variation of the target interval, and the range of the target interval are multiplied to obtain an initial environmental influence coefficient;

[0106] The initial environmental influence coefficient is normalized to obtain the environmental influence coefficient.

[0107] Specifically, the initial environmental influence coefficient is normalized to obtain the environmental influence coefficient, including:

[0108] A linear normalization function is used to normalize the initial environmental influence coefficient to obtain the environmental influence coefficient.

[0109] The number of target thermal response coefficients in the target interval is obtained The number of non-target data points , and the variance of all target thermal response coefficients in the target interval The coefficient of variation of the target interval The calculation formula is: Wherein, is the coefficient of variation of the target interval, is the number of target thermal response coefficients in the target interval, is the number of non-target thermal response coefficients in the target interval, The variance of the target thermal response coefficient in the target interval.

[0110] The proportion of the target thermal response coefficient, the greater the proportion, the more the thermal response coefficient in the target interval is within the current transmission power range, so that the laser emitted by the laser deicing device has less impact on the cable in this time period, so the reference of this data is greater, otherwise, it is the opposite. The volatility of the data, the greater the volatility of the data, the greater the impact of the current transmission power laser on the cable, so the greater the variability of the data.

[0111] A coordinate system is established with each sampling time in the target interval as the horizontal axis and the thermal response coefficient at the sampling time as the vertical axis, the absolute value of the slope between each adjacent target thermal response coefficient is calculated, and the change rate of each adjacent target thermal response coefficient is obtained The average of the change rates of the plurality of adjacent target thermal response coefficients in the target interval is calculated, and the average change rate The difference between the maximum target thermal response coefficient and the minimum target thermal response coefficient in the target interval is calculated, and the range of the target interval is obtained The calculation formula of the environmental influence coefficient

[0112] ;

[0113] Among them, is the environmental influence coefficient, is the coefficient of variation of the target interval, is the average change rate, is the maximum target thermal response coefficient in the target interval, is the minimum target thermal response coefficient in the target interval, is the range of the target interval, is the initial environmental influence coefficient, is a linear normalization function for normalizing the initial environmental influence coefficient to the interval [0, 1].

[0114] The greater the average change rate , the more dramatic the change in data, so the greater the impact of the environment on it during the deicing process; and the range represents the range of influence, the greater the range, the greater the range of influence, so the greater the environmental influence coefficient;

[0115] ​Because the power of the laser emitting device needs to be automatically adjusted, in order to prevent the laser from causing damage to the cable, the predicted laser emitting power of the cable at the deicing position at the next moment needs to be predicted. In the process of prediction, systematic judgment needs to be made according to the real-time changing power to avoid the power being too large or too small, which affects the deicing effect.

[0116] S13, based on the relative deviation degree of the emitting power of each sampling moment in the current interval and the average power in the current interval, and the distance between each sampling moment and the target moment, calculating the first predicted power of the target moment.

[0117] The target moment can be the next moment of the current moment. The prediction in the present application is divided into two stages, one is to take the real-time data of the current interval as a sample to predict the value of the next moment, and the second is to take the historical data of the historical interval as a sample to predict the value of the next moment. Specifically:

[0118] In one embodiment, based on the relative deviation degree of the emitting power of each sampling moment in the current interval and the average power in the current interval, and the distance between each sampling moment and the target moment, the first predicted power of the target moment is calculated, comprising:

[0119] Calculate the ratio of the emitting power of each sampling moment in the current interval to the average power of the current interval to obtain the relative deviation degree of the sampling moment;

[0120] Calculate the distance between each sampling moment in the current interval and the target moment to obtain the interval distance of the sampling moment;

[0121] Calculate the product of the relative deviation degree of each sampling moment and the inverse of the interval distance of the sampling moment to obtain the prediction weight of the sampling moment;

[0122] Calculate the product of the prediction weight of each sampling moment in the current interval and the emitting power of the sampling moment to obtain the predicted power of the sampling moment;

[0123] Calculate the mean value of the predicted power of the plurality of sampling moments in the current interval to obtain the first predicted power of the target moment.

[0124] The calculation formula of the first predicted power of the target moment is: .

[0125] Wherein, is the first predicted power of the target moment, is the number of sampling moments in the current interval, i is the i-th sampling moment in the current interval, is the emitting power of the deicing device of the i-th sampling moment in the current interval, is the average power of the deicing device of the plurality of sampling moments in the current interval. is a relative deviation degree of the i th moment, is an interval distance of the i th sampling moment, that is, a distance between the i th sampling moment and the target moment, is a prediction weight of the i th sampling moment, and +0.01 prevents the denominator from being 0, represents a mapping function or a weighting function used to calculate the weight, and can be a normalization function, which is used to map to the interval [0, 1], if and the greater the ratio of and the greater the ratio of

[0126] S14, based on the influence weight of each sub-interval in the historical interval and the corresponding historical average power, a second predicted power of the target moment is calculated.

[0127] wherein each sub-interval indicates a time interval covered by each cluster after clustering of the historical target thermal response coefficients, and the historical target thermal response coefficients are obtained by screening the thermal response coefficients in the historical interval.

[0128] The influence weight of each sub-interval is determined according to the similarity between the historical target thermal response coefficient of the sub-interval and the thermal response coefficient of the target interval.

[0129] The historical interval can be a continuous interval before the current interval, or a plurality of discontinuous intervals before the current interval, each interval being continuous in itself, and the plurality of intervals being discontinuous or continuous.

[0130] In one embodiment, based on the influence weight of each sub-interval in the historical interval and the corresponding historical average power, a second predicted power of the target moment is calculated, comprising:

[0131] According to the box plot algorithm, a plurality of historical thermal response coefficients in the historical interval are screened, and historical thermal response coefficients less than the quartile are determined as historical target thermal response coefficients;

[0132] A plurality of historical target thermal response coefficients in the historical interval are clustered to obtain a plurality of historical clusters, and a time interval covered by the historical target thermal response coefficients in each cluster is determined as a sub-interval corresponding to the cluster;

[0133] For each sub-interval, a ratio of a number of all historical thermal response coefficients in the sub-interval to a number of historical target thermal response coefficients in the sub-interval is calculated to obtain a proportion of historical target thermal response coefficients in the sub-interval;

[0134] The product of the variance of all historical target thermal response coefficients in the sub-interval and the proportion of the historical target thermal response coefficients in the sub-interval is calculated to obtain the coefficient of variation of the sub-interval; the coefficient of variation of the sub-interval indicates the fluctuation degree of the historical target thermal response coefficients in the sub-interval;

[0135] The historical target thermal response coefficients of each sub-interval are sequenced to obtain the historical target thermal response coefficient sequence of the sub-interval, and the target thermal response coefficients of the target interval are sequenced to obtain the target thermal response coefficient sequence of the target interval;

[0136] The DTW value of the historical target thermal response coefficient sequence of each sub-interval and the target thermal response coefficient sequence of the target interval is calculated to obtain the similarity between the sub-interval and the target interval;

[0137] The distance between the center time of each sub-interval and the center time of the target interval is calculated to obtain the interval distance of the sub-interval;

[0138] The influence weight of the sub-interval is determined according to the reciprocal of the product of the coefficient of variation of each sub-interval, the similarity between the sub-interval and the target interval, and the interval distance of the sub-interval;

[0139] Based on the influence weight of each sub-interval in the historical interval and the corresponding historical average power, the second predicted power at the target time is calculated.

[0140] When predicting the transmit power, first, a plurality of historical thermal response coefficients in a historical interval are obtained, then the plurality of historical thermal response coefficients in the historical interval are screened according to the box plot algorithm, and the historical thermal response coefficients less than the quartile are determined as historical target thermal response coefficients, and the plurality of historical target thermal response coefficients are clustered to obtain a plurality of historical clusters, and the time interval covered by the historical target thermal response coefficients in each cluster is determined as the sub-interval corresponding to the cluster.

[0141] For each sub-interval, the number of non-historical target thermal response coefficients in the sub-interval and the number of historical target thermal response coefficients in the sub-interval are obtained. The formula for calculating the coefficient of variation of the a-th sub-interval is as follows: wherein, is the coefficient of variation of the a-th sub-interval, is the number of non-historical target thermal response coefficients in the a-th sub-interval, is the number of historical target thermal response coefficients in the a-th sub-interval, is the variance of the historical target thermal response coefficients in the a-th sub-interval.

[0142] The historical target thermal response coefficient sequence of each sub-interval is obtained by forming a sequence of the historical target thermal response coefficients of each sub-interval, and the target thermal response coefficient sequence of the target interval is obtained by forming a sequence of the target thermal response coefficients of the target interval. The DTW value of the historical target thermal response coefficient sequence of each sub-interval and the target thermal response coefficient sequence of the target interval is calculated to obtain the similarity between the sub-interval and the target interval The calculation formula of the influence weight of the a-th sub-interval is as follows: , wherein is the influence weight of the a-th sub-interval, is the coefficient of variation of the a-th sub-interval, is the similarity between the a-th sub-interval and the target interval, that is, the DTW value of the historical target thermal response coefficient sequence of the a-th sub-interval and the target thermal response coefficient sequence of the target interval, is the interval distance of the a-th sub-interval, that is, the distance between the center time of the a-th sub-interval and the center time of the target interval, represents an exponential function with a natural constant as the base.

[0143] In an embodiment, the second predicted power at the target time is calculated based on the influence weight of each sub-interval in the historical interval and the corresponding historical average power, and the calculation includes:

[0144] The product of the influence weight of each sub-interval and the historical average power of the sub-interval is calculated to obtain the predicted power of the sub-interval;

[0145] The mean value of the predicted powers of the multiple sub-intervals in the historical interval is calculated to obtain the second predicted power at the target time.

[0146] The calculation formula of the second predicted power at the target time is as follows:

[0147] ;

[0148] , wherein is the second predicted power at the target time, is the number of the multiple sub-intervals in the historical interval, and a is the a-th sub-interval, is the influence weight of the a-th sub-interval, is the historical average power of the a-th sub-interval.

[0149] S15, the current transmitting power is corrected according to the first predicted power, the second predicted power and the environmental influence coefficient to obtain the target power at the target time, and the deicing equipment is controlled to operate at the target power.

[0150] ​​In one embodiment, the current transmitting power is corrected according to the first predicted power, the second predicted power and the environmental influence coefficient to obtain the target power at the target time, and the deicing device is controlled to operate at the target power, including:

[0151] The mean of the first predicted power and the second predicted power is calculated to obtain the predicted power at the target time;

[0152] The difference between the predicted power at the target time and the current transmitting power is calculated to obtain a power difference;

[0153] The product of the power difference and the environmental influence coefficient is calculated to obtain a correction coefficient;

[0154] The mean of the transmitting powers corresponding to the plurality of target thermal response coefficients of the current interval is calculated to obtain the current transmitting power;

[0155] The sum of the correction coefficient and the predicted power at the target time is calculated to obtain the target power at the target time, and the deicing device is controlled to operate at the target power.

[0156] The mean of the laser transmitting powers corresponding to the plurality of target thermal response coefficients of the current interval is calculated to obtain the current transmitting power The mean of the first predicted power and the second predicted power is calculated to obtain the predicted power at the target time, and the calculation formula of the predicted power at the target time is: .

[0157] However, the distribution of ice and snow on the cable is not uniform, and in the process of snow removal, the ice and snow on the cable may fall due to wind blowing, shaking, etc. In order to avoid damaging the cable, the predicted value needs to be balanced, so the environmental influence coefficient obtained according to the above calculation is used to balance the predicted power.

[0158] Therefore, the difference between the predicted power at the target time and the current transmitting power is calculated to obtain a power difference , the product of the power difference and the environmental influence coefficient is calculated to obtain a correction coefficient , the sum of the correction coefficient and the predicted power at the target time is calculated to obtain the target power at the target time, and the calculation formula of the target power at the target time is: , wherein, is the target power at the target time, is the predicted power at the target time, is the current transmitting power, is the environmental influence coefficient.​​

[0159] The difference between the ideal value and the actual value, the larger the difference, the greater the current required laser power, but at this time the influence factors of the environment is small, then need to adjust the laser power to small, the opposite to large adjustment. For positive, the actual laser power demand is larger; but for balance, it needs to be adjusted to small; if For negative, the actual laser power demand is less than the target value, then the whole is adjusted to small.

[0160] According to the target power obtained above, real-time adjustment is carried out, and then the line is deiced. The process is as follows:

[0161] First step: target identification and positioning The operator searches for the iced line in a large range by using the visible light camera through the control unit. Image recognition algorithm can assist in automatically identifying the conductor. The system aims the deicing system at the target line through the precision gimbal.

[0162] Second step: safety confirmation and preliminary aiming A low-power, visible indication laser (usually coaxial with the main laser) is emitted to form a spot on the target point. The operator confirms through the high-definition video that the spot is accurately on the ice of the conductor, not on the conductor itself or adjacent towers, insulators and other key components, to ensure safety.

[0163] Third step: parameter initialization and exploration The system adjusts the laser focusing according to the range finder data. The control unit sets a conservative initial laser power according to the preset ice condition model (such as ice thickness, environmental temperature). At the same time, the infrared temperature measurement system starts to work and records the initial surface temperature of the cable.

[0164] Fourth step: closed-loop control and deicing (core link) The system emits laser and immediately enters the intelligent closed-loop control cycle. The core of this cycle is "perception-decision-execution". In the closed-loop deicing process, the control unit dynamically calculates the target power based on the real-time collected thermal response characteristics, through the fusion of current trend prediction, historical similar working conditions and environmental influence coefficient, and adjusts the laser output to realize adaptive deicing control.

[0165] Fifth step: scanning and coverage Once the ice layer at the current point is removed, the control unit will instruct the gimbal to move the laser beam along the conductor direction to scan to the adjacent non-deicing section, and repeat the above closed-loop deicing process until the ice on the entire line is completely removed.

[0166] Sixth step: operation end and record After deicing, the system generates an operation report including deicing line position, time consumption, energy consumption and other data, and saves the whole temperature record for post-analysis and system optimization.

[0167] The application accurately defines a target interval representing a stable working condition by dynamically screening and clustering target thermal response coefficients, and determines a precise quantitative environmental influence coefficient based on the change rate, maximum value and dispersion of the thermal response coefficients in the target interval, so as to realize adaptive perception of environmental interference. By fusing local trend prediction based on the current interval power relative deviation and time distance and global experience prediction based on historical interval similarity weighted matching, and introducing the environmental influence coefficient for collaborative correction, the target power that can respond to real-time working condition changes and historical experience rules at the same time is finally generated. The contradiction between deicing efficiency and cable safety caused by uneven ice distribution and environmental fluctuations during laser deicing in high-cold environment is effectively overcome. On the premise of ensuring no damage to the cable, rapid, adaptive and high-precision removal of the ice on the power transmission line is realized, and the safety, efficiency and intelligent level of the deicing operation are significantly improved.

[0168] It should be understood that, although Figure 1 The steps in the flowchart of the application are displayed in sequence according to the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, the execution of these steps is not strictly limited in sequence, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps in the application can include multiple sub-steps or multiple stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least part of other steps or sub-steps or stages of other steps.

[0169] The application also provides a long-distance laser deicing system for power transmission lines in high-cold regions, as shown in Figure 2 The system comprises:

[0170] A clustering module 21 is configured to cluster a plurality of target thermal response coefficients to obtain a target cluster; the target thermal response coefficients are obtained by screening the thermal response coefficients in the current interval; the thermal response coefficient indicates the ratio of the transmission power of the deicing device to the temperature of the cable;

[0171] An analysis module 22 is configured to analyze the change rate of a plurality of adjacent target thermal response coefficients in the target interval, the maximum value of the target thermal response coefficients in the target interval, and the dispersion of the target thermal response coefficients in the target interval, and determine an environmental influence coefficient; the target interval is determined according to the interval covered by the sampling time of each target thermal response coefficient in the target cluster;

[0172] The first calculation module 23 is configured to calculate the first predicted power of the target time point based on the relative deviation degree of the transmission power of each sampling time point in the current interval from the average power in the current interval and the distance between each sampling time point and the target time point.

[0173] The second calculation module 24 is configured to calculate the second predicted power of the target time point based on the influence weight of each sub-interval in the history interval and the corresponding historical average power. Each sub-interval indicates the time interval covered by each cluster after clustering of the historical target thermal response coefficients. The historical target thermal response coefficients are obtained by screening the thermal response coefficients in the history interval. The influence weight of each sub-interval is determined according to the similarity between the historical target thermal response coefficients of the sub-interval and the thermal response coefficients of the target interval.

[0174] The correction module 25 is configured to correct the current transmission power according to the first predicted power, the second predicted power and the environmental influence coefficient, to obtain the target power of the target time point, and control the deicing device to operate at the target power.

[0175] For the system embodiment, since it basically corresponds to the method embodiment, the relevant parts are described in the method embodiment. The above-described system embodiment is only illustrative, and the units described as separate components can or can not be physically separated, and the components of the unit can or can not be physical units, i.e., they can be located in one place or distributed on multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the present application.

[0176] Figure 3 A structure diagram of an electronic device is shown for an example embodiment of the present application, which includes a memory, a processor and a computer program stored in the memory and used to run on the processor. When the processor executes the computer program, the method described in any of the above embodiments is implemented. Figure 3 The electronic device 30 shown is only an example and should not limit the function and use range of the embodiments of the present application.

[0177] As shown in Figure 3 The electronic device 30 can be in the form of a general computing device, for example, it can be a server device. The components of the electronic device 30 can include but are not limited to the above-mentioned at least one processor 31, the above-mentioned at least one memory 32, the bus 33 connecting different system components including the memory 32 and the processor 31.

[0178] The bus 33 includes a data bus, an address bus and a control bus.

[0179] The memory 32 can include volatile memory, such as random access memory (RAM) 321 and / or cache memory 322, and / or non-volatile memory, such as read only memory (ROM) 323.

[0180] The memory 32 can include a program tool 325 (or utility tool) having a set of one or more program modules 324, including but not limited to an operating system, one or more application programs, other program modules, and program data, and each of such examples, or some combination thereof, can include implementation of a network environment.

[0181] The processor 31, through the running of the computer program stored in the memory 32, can execute various function applications and data processing, such as the method provided by any of the above embodiments.

[0182] The electronic device 30 can also communicate with one or more external devices 34 (such as a keyboard or a pointing device, etc.) through an input / output (I / O) interface 35. In addition, the electronic device 30 can also communicate with one or more networks (such as a local area network (LAN), a wide area network (WAN), and / or a public network such as the Internet) through a network adapter 36. As shown, the network adapter 36 communicates with other modules of the electronic device 30 through the bus 33. It should be understood that although not shown in the figure, other hardware and / or software modules can be used in conjunction with the electronic device 30, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID (Redundant Array of Independent Disks) systems, tape drives, and data backup storage systems, etc.

[0183] It should be noted that although several units / modules or sub-units / modules of the electronic device are mentioned in the above detailed description, such division is merely exemplary and not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided into multiple units / modules.

[0184] The embodiments of the present application also provide a computer readable storage medium, which stores a computer program, and the program is executed by a processor to implement the method provided by any of the above embodiments.

[0185] More specifically, the readable storage medium can include, but is not limited to: a portable disc, a hard disk, a random access memory, a read only memory, an erasable programmable read only memory, an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0186] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiments of the methods can be included. Any reference to memory, storage, database, or other medium used in the embodiments provided in the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0187] The embodiments of the present application also provide a computer program product comprising a computer program, which, when executed by a processor, implements the method of any one of the above.

[0188] The program code of the computer program product for executing the present application can be written in any combination of one or more programming languages, and can be executed completely on a user device, partially on a user device, as an independent software package, partially on a user device and partially on a remote device, or completely on a remote device.

[0189] The technical features of the above embodiments can be combined in any manner. To make the description concise, not all possible combinations of the technical features in the above embodiments are described, but as long as the combinations of the technical features do not contradict, they should be considered within the scope of the present application.

[0190] The above embodiments only express several implementation manners of the present application, and the description is more specific and detailed, but it should not be understood as a limitation on the scope of the application. It should be pointed out that for those skilled in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which are within the scope of the present application.

[0191] The various embodiments described in this specification are presented by way of example, and each embodiment is not inherently more important than any other embodiment.

Claims

1. A method for long-distance laser de-icing of power transmission lines in cold regions, characterized in that, The method includes: Multiple target thermal response coefficients are clustered to obtain target clusters; the target thermal response coefficients are obtained by filtering the thermal response coefficients in the current interval, and the thermal response coefficient indicates the ratio of the de-icing equipment's transmission power to the cable temperature; The environmental impact coefficient is determined by analyzing the rate of change of thermal response coefficients of multiple adjacent targets in the target interval, the maximum and minimum values ​​of thermal response coefficients of targets in the target interval, and the dispersion of thermal response coefficients of targets in the target interval; the target interval is determined based on the interval covered by the sampling time of thermal response coefficients of each target in the target cluster. Based on the relative deviation between the transmit power at each sampling time within the current interval and the average power within the current interval, and the distance between each sampling time and the target time, the first predicted power at the target time is calculated. The second predicted power at the target time is calculated based on the influence weight of each sub-interval in the historical interval and its corresponding historical average power. Each sub-interval indicates the time interval covered by each cluster after the historical target thermal response coefficient is clustered. The historical target thermal response coefficient is obtained by screening the thermal response coefficients in the historical interval. The influence weight of each sub-interval is determined based on the similarity between the historical target thermal response coefficient of the sub-interval and the thermal response coefficient of the target interval. Based on the first predicted power, the second predicted power, and the environmental impact coefficient, the current transmission power is corrected to obtain the target power at the target time, and the de-icing equipment is controlled to operate at the target power.

2. The long-distance laser de-icing method for power transmission lines in high-altitude and cold regions as described in claim 1, characterized in that, Before clustering multiple target thermal response coefficients to obtain target clusters, the process also includes: At each sampling moment in the current interval, the temperature of the cable and the transmission power of the de-icing device are acquired, and the ratio of the transmission power of the de-icing device to the temperature of the cable is calculated to obtain the thermal response coefficient at each sampling moment; the current interval includes the current moment and multiple sampling moments before it. Calculate the mean of multiple thermal response coefficients in the current interval to obtain the mean thermal response. Calculate the difference between each thermal response coefficient and the mean thermal response value in the current interval to obtain the thermal response difference of that thermal response coefficient; Based on the box plot algorithm, multiple thermal response differences in the current interval are filtered, and the thermal response coefficients corresponding to thermal response differences less than the interquartile are determined as the target thermal response coefficients.

3. The long-distance laser de-icing method for power transmission lines in high-altitude and cold regions as described in claim 1, characterized in that, The clustering of multiple target thermal response coefficients to obtain target clusters includes: Hierarchical clustering is performed on multiple target thermal response coefficients in the current interval to obtain multiple clusters; The cluster with the largest number of target thermal response coefficients is identified as the target cluster.

4. The long-distance laser de-icing method for power transmission lines in high-altitude and cold regions as described in claim 1, characterized in that, The analysis of the rate of change of thermal response coefficients of multiple adjacent targets within the target interval, the maximum and minimum values ​​of the thermal response coefficients within the target interval, and the dispersion of the thermal response coefficients within the target interval, to determine the environmental impact coefficient, includes: Calculate the ratio of the total number of thermal response coefficients in the target interval to the total number of target thermal response coefficients in the target interval to obtain the proportion of target thermal response coefficients in the target interval; The coefficient of variation of the target interval is obtained by multiplying the variance of all target thermal response coefficients in the target interval by the proportion of the target thermal response coefficients in the target interval. The coefficient of variation of the target interval indicates the volatility of the target thermal response coefficients within the target interval. The dispersion of the target thermal response coefficients in the target interval includes the coefficient of variation of the target interval. A coordinate system is established with each sampling time in the target interval as the horizontal axis and the thermal response coefficient at that sampling time as the vertical axis. The absolute value of the slope between each adjacent target thermal response coefficient is calculated to obtain the rate of change of each adjacent target thermal response coefficient. The environmental impact coefficient is determined by analyzing the mean rate of change of thermal response coefficients of multiple adjacent targets in the target interval, the coefficient of variation of the target interval, and the maximum and minimum values ​​of thermal response coefficients of the targets in the target interval. The environmental impact coefficient indicates the degree of influence of the environment on the de-icing equipment.

5. The long-distance laser de-icing method for power transmission lines in high-altitude and cold regions as described in claim 4, characterized in that, The analysis of the mean rate of change of thermal response coefficients of multiple adjacent targets within the target interval, the coefficient of variation of the target interval, and the extreme values ​​of the thermal response coefficients within the target interval, to determine the environmental impact coefficient, includes: Calculate the difference between the maximum and minimum target thermal response coefficients within the target range to obtain the range of the target range; The initial environmental impact coefficient is obtained by multiplying the mean rate of change of thermal response coefficients of multiple adjacent targets in the target interval, the coefficient of variation of the target interval, and the range of the target interval. The initial environmental impact coefficient is normalized to obtain the environmental impact coefficient.

6. The long-distance laser de-icing method for power transmission lines in high-altitude and cold regions as described in claim 5, characterized in that, The normalization process for the initial environmental impact coefficient to obtain the environmental impact coefficient includes: The initial environmental impact coefficient is normalized using a linear normalization function to obtain the environmental impact coefficient.

7. The long-distance laser de-icing method for power transmission lines in high-altitude and cold regions as described in claim 1, characterized in that, The calculation of the first predicted power at the target time based on the relative deviation between the transmit power at each sampling time within the current interval and the average power within the current interval, and the distance between each sampling time and the target time, includes: Calculate the ratio of the transmit power at each sampling moment in the current interval to the average power of the current interval to obtain the relative deviation at that sampling moment; Calculate the distance between each sampling time and the target time in the current interval to obtain the interval distance of that sampling time; The prediction weight for each sampling moment is obtained by multiplying the relative deviation at each sampling moment by the reciprocal of the interval distance at that sampling moment. Calculate the product of the prediction weight at each sampling time in the current interval and the transmit power at that sampling time to obtain the prediction power corresponding to that sampling time; Calculate the mean of the predicted power at multiple sampling times in the current interval to obtain the first predicted power at the target time.

8. The method for long-distance laser de-icing of power transmission lines in high-altitude and cold regions as described in claim 1, characterized in that, The calculation of the second predicted power at the target time based on the influence weights of each sub-interval in the historical interval and their corresponding historical average power includes: Based on the box plot algorithm, multiple historical thermal response coefficients in the historical interval are screened, and the historical thermal response coefficients less than the interquartile range are determined as the historical target thermal response coefficients. Clustering of multiple historical target thermal response coefficients in the historical interval yields multiple historical clusters. The time interval covered by the thermal response coefficients of the historical targets in each cluster is determined as the sub-interval corresponding to that cluster. For each sub-interval, calculate the ratio of the number of all historical thermal response coefficients in that sub-interval to the number of historical target thermal response coefficients in that sub-interval, and obtain the proportion of historical target thermal response coefficients in that sub-interval. The coefficient of variation for a sub-interval is obtained by multiplying the variance of all historical target thermal response coefficients in the sub-interval with the proportion of historical target thermal response coefficients in the sub-interval. The coefficient of variation for a sub-interval indicates the volatility of historical target thermal response coefficients within that sub-interval. The historical target thermal response coefficients of each sub-interval are combined into a sequence to obtain the historical target thermal response coefficient sequence of that sub-interval. The target thermal response coefficients of the target interval are combined into a sequence to obtain the target thermal response coefficient sequence of the target interval. Calculate the DTW value of the historical target thermal response coefficient sequence of each sub-interval and the target thermal response coefficient sequence of the target interval to obtain the similarity between the sub-interval and the target interval; Calculate the distance between the center time of each sub-interval and the center time of the target interval to obtain the interval distance of that sub-interval; The influence weight of a sub-interval is determined by multiplying the coefficient of variation of each sub-interval, the similarity between the sub-interval and the target interval, and the negative of the cumulative product of the interval distance of the sub-interval. The second predicted power at the target time is calculated based on the influence weights of each sub-interval in the historical interval and their corresponding historical average power.

9. The long-distance laser de-icing method for power transmission lines in high-altitude and cold regions as described in claim 8, characterized in that, The calculation of the second predicted power at the target time based on the influence weights of each sub-interval in the historical interval and their corresponding historical average power includes: The predicted power of a sub-interval is obtained by multiplying the influence weight of each sub-interval by the historical average power of that sub-interval. The average of the predicted power of multiple sub-intervals in the historical interval is calculated to obtain the second predicted power at the target time.

10. The long-distance laser de-icing method for power transmission lines in high-altitude and cold regions as described in claim 1, characterized in that, The step of correcting the current transmission power based on the first predicted power, the second predicted power, and the environmental impact coefficient to obtain the target power at the target time, and controlling the de-icing equipment to operate at the target power, includes: Calculate the average of the first and second predicted powers to obtain the predicted power at the target time; The power difference is obtained by calculating the difference between the predicted power at the target time and the current transmission power. The correction factor is obtained by multiplying the power difference by the environmental impact coefficient. Calculate the average of the transmission power corresponding to the thermal response coefficients of multiple targets in the current interval to obtain the current transmission power; The target power at the target time is obtained by summing the correction coefficient with the predicted power at the target time, and the de-icing equipment is controlled to operate at the target power.

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