100 results about "Ice thickness" patented technology

The invention is suitable for the technical field of power transmission line maintenance, and provides a line early warning judgment method and system based on multi-source data fusion, and the method comprises the steps: constructing a multi-dimensional knowledge graph, and building a semantic association network; collecting meteorological and equipment state data in real time, fusing the data into a knowledge graph space through a mapping function, identifying an abnormal meteorological-equipment combination mode by using fuzzy reasoning, and calculating a thickness change rate in combination with an icing growth prediction model; the icing thickness and the galloping probability are calculated, and a composite early warning level is generated; and dynamically generating a risk thermodynamic diagram on the GIS map, and visually displaying a risk propagation path. Through semantic fusion of multi-source data, composite risk modeling and spatialization decision making, the system breaks through single parameter criterion limitation of traditional early warning, realizes intelligent identification and dynamic early warning of meteorological-equipment coupling risks, and significantly improves accuracy of power transmission line disaster early warning and operation and maintenance decision making efficiency.

The invention relates to the technical field of railway contact networks, and provides a railway contact network icing thickness prediction method and system. The method comprises the following steps: inputting meteorological environment parameters into a machine learning model, and carrying out dynamic calibration on icing medium parameters based on the meteorological environment parameters by utilizing the machine learning model to obtain calibrated icing medium parameters; obtaining an icing growth coefficient based on the meteorological environment parameters, the conductor physical characteristic parameters and the calibrated icing medium parameters; and inputting the calibrated icing medium parameters and the icing growth coefficient into a Makkonen model to obtain an icing thickness prediction value. According to the technical scheme provided by the invention, the key icing parameters are dynamically calibrated through machine learning, and the computational logic of the Makkonen model is optimized, so that the icing thickness prediction precision under complex meteorological conditions is improved, and the problem of prediction failure caused by insufficient environmental adaptability of a traditional static model is solved.

The invention relates to the technical field of fan blade deicing, and discloses an intelligent temperature control type fan blade electric heating deicing control system and method, and the system comprises a meteorological sensing module which is used for collecting the environment temperature, humidity, wind speed and rainfall type; the blade state monitoring module is used for acquiring blade surface temperature distribution and ice layer thickness data; the dynamic decision-making module is used for generating a partition heating instruction based on the data of the weather sensing module and the blade state monitoring module; the temperature control execution module is used for converting the instruction into a gradient signal; the heating array module is used for executing electric heating deicing operation in the blade surface subareas; and the energy coordination module is used for dynamically constraining the total power of the system. The meteorological sensing module and the blade state monitoring module are integrated through the system, real-time collection and fusion of multi-source data of blade surrounding environment parameters and the thickness of an ice layer are achieved through the design, comprehensiveness and accuracy of icing monitoring are improved, a reliable basis is provided for dynamic decision making, and therefore the response capacity and early warning precision of the system to icing risks are improved.

The invention discloses an ice condition prediction method based on multi-feature fusion and physical constraint, and belongs to the technical field of hydrological forecasting. Firstly, various types of data of a target area are collected and preprocessed to serve as a data set, features of the various types of data are extracted, feature fusion is conducted on obtained image features, time sequence features and environment features through a multi-head attention mechanism, and a fusion feature vector is generated. Secondly, adopting a physical information neural network model, taking the fusion feature vector as input, taking ice thickness and ice stress as output layers, carrying out constraint by using a composite loss function, carrying out model optimization by using a verification set, carrying out processing through a full connection layer in the network, and carrying out end-to-end training and regularization of a prediction model; and finally, evaluating the final prediction model obtained by training through the test set, and verifying the effectiveness and generalization ability of the final prediction model. The method combines multi-source and multi-mode observation data, can effectively capture complex relations between ice surface changes and various factors, can improve prediction precision, stability and reliability, and can improve model training efficiency and generalization ability.

The invention discloses an icing prediction method and system based on terrain potential energy field and multi-scale meteorological coupling, relates to the technical field of power transmission line icing prediction, and solves the problems that a traditional icing thickness prediction model is split and traditional static terrain parameters cannot represent dynamic terrain potential energy. According to the technical scheme, the method comprises the following steps: acquiring meteorological data and high-resolution digital elevation data; calculating a topographic potential energy tensor; establishing a multi-meteorological coupling model, and correcting the multi-meteorological coupling model through the topographic potential energy tensor; carrying out meteorological element correction on the corrected multi-meteorological coupling model to obtain a corrected meteorological field; and obtaining a first icing thickness prediction value and a second icing thickness prediction value based on a pre-constructed icing growth physical model and a pre-trained machine learning model, and carrying out weighted calculation on the first icing thickness prediction value and the second icing thickness prediction value to obtain a final icing thickness prediction value. And the effect of improving the prediction precision under complex terrain and extreme meteorological conditions is achieved.

The invention relates to the technical field of power transmission lines, in particular to a power transmission line disaster toughness digital design method, which comprises the following steps: acquiring real-time environment parameters of a power transmission line, and calculating a comprehensive risk index based on the real-time environment parameters; calculating a ratio of an icing thickness change rate to a historical same-period average change rate based on the icing thickness sequence to obtain an icing risk index; obtaining a difference value sequence of galloping amplitudes of the power transmission line in adjacent monitoring time periods, and calculating a ratio of a variance of the difference value sequence to a historical galloping variance mean value to obtain a galloping risk index; and generating a comprehensive disaster early warning level based on the icing risk index and the galloping risk index, and adjusting a current load limit value of the power transmission line based on the comprehensive disaster early warning level. The unmanned aerial vehicle is used for monitoring the icing thickness, the vibration sensor is used for monitoring the galloping amplitude, different factors possibly influencing the safety of the power transmission line are comprehensively captured, and the comprehensiveness and accuracy of disaster early warning are improved through multi-dimensional monitoring.

The invention discloses a fan blade detecting and deicing system and method. The fan blade detecting and deicing system comprises a detecting unit, a deicing unit and a control unit. The detection unit comprises an icing detection assembly, an icing thickness detector and a temperature sensor are arranged in the icing detection assembly, the icing thickness detector detects icing thickness data of the blade surface in real time, and the temperature sensor detects temperature data of the fan blade surface in real time; the deicing unit comprises an electric heating film which is at least laid on the front edge of the blade in the length direction of the blade. And the control unit comprehensively analyzes the icing thickness and temperature change condition corresponding to the whole blade according to the icing thickness data and temperature data of the blade surface, and independently triggers and controls the heating state of each blade deicing unit based on the comprehensive analysis result. According to the fan blade detecting and deicing system and method, the precise monitoring function, the intelligent deicing strategy and stable and safe operation are integrated, and the wide application and popularization value is achieved.

The invention provides an icing thickness detection method, a laser ranging device and a system, and relates to the technical field of high-voltage line monitoring, and the method comprises the steps: mounting the laser ranging device on an unmanned aerial vehicle, and enabling the unmanned aerial vehicle to hover above a power transmission conductor based on an RTK differential positioning technology; adjusting flight parameters of the unmanned aerial vehicle based on a visual identification algorithm, so that the laser ranging device is mounted on the power transmission conductor and is aligned with the target measurement position; starting a laser ranging device, and collecting surface icing thickness data and ice layer surface temperature data of the power transmission conductor; and performing fusion processing on the measurement data based on a Kalman filtering algorithm, and outputting processed icing thickness data. The method can accurately position the unmanned aerial vehicle, ensures that the laser ranging device accurately aligns to the target measurement point, and improves the autonomous operation capability of the system; the laser ranging device is used for obtaining multiple types of data and performing fusion analysis, the measurement precision is improved, it can be ensured that high-precision measurement is achieved in the live-line state of the transmission conductor, and the safety risk is reduced.

The invention discloses a simplified test natural river ice section flow calculation method, which belongs to the technical field of hydrological test, and comprises the following steps: dividing a section into a plurality of strip units; calculating the effective water depth of each measuring point according to the water depth and the water immersion ice thickness of the measuring point corresponding to each strip unit; calculating the area of each strip unit according to the effective water depth at each measuring point; according to the area of each strip unit, the accumulated section area and the accumulated hydraulic radius from the left bank and the right bank of the section to the strip units are calculated respectively; according to the accumulated section area and the accumulated hydraulic radius from the left bank and the right bank of the section to the strip unit, the relative unit width flow of the sections on the left side and the right side of the strip unit is calculated, and then the comprehensive relative unit width flow of the strip unit is calculated; and calculating the total flow of the section according to the proportional relation between the comprehensive relative unit width flow and the actual unit width flow of the strip unit. According to the method, the full-section flow can be reversely deduced through a small amount of observation, so that the ice period flow testing process is simplified.

The invention discloses a power distribution overhead line icing thickness detection method, system and device and a storage medium, and relates to the field of icing thickness detection.The method comprises the steps that multi-source detection data of a power distribution overhead line is collected, self-adaptive interpolation completion is conducted based on data distribution characteristics, for example, bilinear interpolation is conducted on a two-dimensional image, linear interpolation is conducted on sequence data, and the detection result is obtained; complementing point cloud data in combination with information such as wind direction; performing multi-source icing thickness detection on the detection data set, and calculating a detection sequence based on image pixel gradient, point cloud intensity and the like; performing multi-source fusion by adopting Bayesian inference to obtain an accurate detection value and a confidence interval; predicting an icing trend in combination with historical data, and performing real-time monitoring and early warning; according to the invention, image edges and ice layer boundaries can be protected, so that interpolation better conforms to physical phenomena, and the detection precision is improved; icing thickness features are described from different aspects, posterior probability distribution can be updated by combining prior and real-time information, the icing thickness is accurately estimated, uncertainty is quantified, and powerful support is provided for decision making.

The invention discloses an ice layer thickness measuring method and device and relates to the field of radar technology and electromagnetism. According to an existing ice thickness detection technology, additional instruments need to be arranged on an ice cover, the complexity and cost of equipment are increased, the requirement for the environment is high, and in order to solve the technical defects existing in the prior art, the technical scheme provided by the invention is that the ice layer thickness measurement method comprises the steps of collecting a preset algorithm and algorithm parameters; a step of preprocessing the collected high-frequency electromagnetic wave echo signal according to the preset algorithm; carrying out peak detection on the preprocessed high-frequency electromagnetic wave echo signal; a step of obtaining a horizon detection result of the preprocessed high-frequency electromagnetic wave echo signal according to a peak value detection result; and obtaining the thickness of the ice layer according to the result of the layer position detection. The method can be applied to ice layer thickness measurement and ice cover bearing capacity calculation.

The invention discloses a power transmission line icing analysis method and system influenced by microtopography and micrometeorology, and relates to the technical field of power transmission line risk prediction.The method comprises the steps that original meteorological data of an area where a power transmission line is located is collected and fused, and micrometeorological field variables are generated based on topographic parameters extracted by a DEM; on the basis of the fusion data and the micrometeorological field variables, three-dimensional micrometeorological field data are obtained through a fluid mechanics model, the three-dimensional micrometeorological field data are corrected through terrain parameters obtained through a DEM model, an exponential weighted moving average method is used for adjustment, and accurate three-dimensional micrometeorological field data are obtained; based on the accurate micrometeorological field data, the icing thickness is obtained by adopting a physical-empirical hybrid icing growth model, the output icing thickness is adjusted in real time through a dynamic correction algorithm, and a final icing simulation result is obtained. The accuracy of power transmission line icing disaster prediction and the flexibility of emergency response are improved.

The invention discloses a measuring device and method for detecting the thickness of an ice layer through a temperature sensor. The device comprises a temperature probe, a data processing module, a communication module and a power supply module, the temperature probe comprises a pipeline and a plurality of temperature sensors arranged in the pipeline, the output ends of the temperature sensors are connected with the input end of the data processing module, and the communication module is connected with the data processing module; the method comprises the following steps: acquiring temperature data; calculating the temperature gradient of the ice layer and the temperature gradient of the water layer; determining the position of 0 DEG C; and calculating interfaces between air and ice / water and between ice and water so as to determine the thickness of the ice layer. The ice layer thickness is detected through networking of the temperature sensors, large-area monitoring can be achieved, and the ice layer thickness monitoring device has the advantages of being low in cost, high in precision and capable of achieving real-time monitoring, can be used for monitoring the ice layer thickness and has important application value for meteorological research, on-ice activities and production operation.

The embodiment of the invention provides an icing thickness prediction method, device and equipment based on multi-source data. The method comprises the following steps: acquiring meteorological data, state data and an icing image of a target power transmission line at a target moment; based on a preset prediction model, according to the meteorological data, determining an icing potential factor at the target moment; based on a preset prediction model, according to the icing potential factor, the meteorological data, the state data and the icing image, obtaining fusion features of icing; wherein the fusion feature is used for representing a nonlinear relationship between the icing influence factors; and on the basis of the prediction model, according to the fusion features, predicting the icing thickness of the target power transmission line. The method is used for achieving the effect of improving the icing thickness prediction accuracy.

Mobile platform for measuring flow velocity, ice thickness and water depth across ice, comprising a carriage (6) equipped with an angle controller (5), wherein an ice thickness and water depth transmitter (1) and a flow velocity transmitter (2) are each mounted on a lifting device (3), wherein a heating device (4) is provided at the bottom of the lifting device (3); wherein the lifting device (3) on which the ice thickness and water depth transmitter (1) are arranged is mounted directly on the carriage (6), and the lifting device (3) on which the flow velocity transmitter (2) is arranged is mounted on the angle controller (5).

The present application relates to the technical field of railway contact networks, and provides a method and system for predicting ice thickness of railway contact networks. The method comprises: inputting meteorological environment parameters into a machine learning model, using the machine learning model to dynamically calibrate the ice medium parameters based on the meteorological environment parameters, and obtaining calibrated ice medium parameters; obtaining an ice growth coefficient based on the meteorological environment parameters, the physical characteristic parameters of the conductor, and the calibrated ice medium parameters; and inputting the calibrated ice medium parameters and the ice growth coefficient into a Makkonen model to obtain an ice thickness prediction value. The technical solution provided by the present application improves the accuracy of ice thickness prediction under complex meteorological conditions by dynamically calibrating key ice parameters through machine learning and optimizing the calculation logic of the Makkonen model, thereby solving the problem of prediction failure caused by insufficient environmental adaptability of traditional static models.

This invention discloses a method and system for identifying ice thickness using a power line de-icing robot, relating to the field of power transmission line maintenance technology. The method includes: determining whether to adjust the perception mode based on ambient lighting conditions; initiating an active enhanced perception process based on the adjustment requirement to acquire image data containing feature differences of the target object; acquiring the three-dimensional geometric information of the target object; determining the geometric contour of the target object by combining the three-dimensional geometric information with the image data; calculating the thickness information of the target object based on the geometric contour; and obtaining the distribution of the target object by combining the position information of the power line de-icing robot. This application can obtain the continuous distribution and morphology of the overall ice on the power line, rather than single-point local information, thereby ensuring the accuracy and reliability of the final thickness calculation and improving the accuracy and timeliness of de-icing operations.

The invention relates to the field of sea ice thickness measurement, in particular to a sea ice thickness measuring device based on an icebreaker, which comprises a mounting part, an outward extending part is arranged in the mounting part, a micro moving part is arranged in the outward extending part, a lifting part is arranged in the micro moving part, a measuring part is arranged in the lifting part, and the measuring part is provided with a snow cleaning chassis. The bottom of the probe rod is fixedly connected with six scrapers which are circumferentially distributed, the scrapers are used for rapidly cleaning a snow accumulation layer and floating ice impurities in a to-be-measured area, the surface of the ice layer is completely exposed, when the probe rod makes contact with the ice layer, a signal is immediately fed back to an external control assembly, the downward moving cylinder body is controlled to stop descending, and it is ensured that the ice thickness measurer only conducts thickness measurement from the surface of the ice layer. And the problems that the ice layer and the accumulated snow layer are difficult to effectively distinguish and the accumulated snow thickness is easy to be included into the sea ice thickness measurement result by utilizing an intelligent sensor and a sound wave type measurement technology are effectively avoided.

This invention proposes an icebreaking device, vessel, and method combining jet-resonance technology for ice-trapped vessels, relating to the field of polar icebreaking technology. It addresses the problem of conventionally powered vessels or icebreakers with low ice levels struggling to break through ice in areas with ice thickness greater than 1.2 meters. It includes a hoisting platform, a jet icebreaking module, a resonant icebreaking module, and an attachment stabilization module. The hoisting platform is used for assembly with an external crane. The jet icebreaking module outputs water jets to break the ice. The resonant icebreaking module induces resonance in the ice layer. The attachment stabilization module includes a helical anchor bolt and a power mechanism. The power mechanism drives the helical anchor bolt to rotate relative to the hoisting platform, and the helical anchor bolt drills into the ice surface to fix the hoisting platform. It is primarily used on polar vessels to break through ice and escape when a vessel is trapped.

The invention relates to the field of sea ice remote sensing, and discloses a sea ice thickness measuring method based on solar microwave radiation enhancement, which comprises the following specific steps of: calculating a solar altitude angle and an azimuth angle at a current position and moment; setting a microwave radiometer overlook sea ice area based on the solar altitude angle and the azimuth angle, and receiving a reflection signal of solar microwave heat radiation; extracting the relative propagation delay inequality of the reflected signal; and calculating the thickness of the sea ice according to the relative propagation delay inequality. The ice thickness is measured by using the characteristics of strong solar microwave radiation and related reception, the problem that the sun is regarded as a harmful factor in the existing remote sensing technology is solved, and the method has the characteristic of being capable of reducing data acquisition and processing pressure.

This utility model discloses a novel ice condition monitoring skateboard, relating to the field of emergency disaster prevention technology. Specifically, it is a novel ice condition monitoring skateboard comprising a skateboard body, a track assembly mounted on the lower front end of the skateboard body, a pivot connecting the track assembly and the skateboard body, and a high-definition infrared camera mounted on the upper front end of the skateboard body. Inside the skateboard body, from front to rear, are a controller, a battery, and an ice and snow radar. Through the track assembly and ice and snow radar, this novel ice condition monitoring skateboard can automatically and quickly detect ice thickness. The coordinated arrangement of the track assembly, high-definition infrared camera, ice and snow radar, temperature sensor, and humidity sensor enables the skateboard to obtain dynamic video of ice surface changes and their relationship with ambient temperature and humidity at close range, providing accurate predictions for the development trend of subsequent ice jams.

The invention discloses an ice vibration response spectrum analysis method and system based on sea ice parameter distribution characteristics, and relates to the field of ice engineering calculation analysis, and the method comprises the steps: constructing an offshore wind turbine motion control equation of a single-degree-of-freedom system under the action of sea ice, and obtaining the power spectrum density of a dynamic ice load; based on compression strength and bending strength of sea ice, a joint probability density function of ice thickness and ice speed is obtained, and an ice area is partitioned; ice force time history samples are obtained, corresponding acceleration response spectrums are deduced and established according to different divided ice areas, and equivalent sea ice force acting on a single-degree-of-freedom system is obtained; and maximum data of all response spectrum curves of different sea ice time history samples in each ice area are taken, and a segmented fitting method is adopted to obtain a design response spectrum of sea ice force. The dynamic ice force time history and the dynamic response of the offshore wind turbine can be quickly and accurately obtained under different sea ice parameters, and technical support is provided for ice-resistant design of an offshore structure.

Embodiments of the present application provide a method, device, and storage medium for determining the ice thickness of a power transmission line. The method includes: obtaining a current microwave transmission signal and a current microwave reception signal collected by a microwave sensor; determining the current ice thickness of the power transmission line based on a first phase of the current microwave transmission signal and a second phase of the current microwave reception signal; obtaining the historical ice thickness of the power transmission line at a previous moment and determining the current ice change rate of the power transmission line; obtaining meteorological data monitored by a meteorological sensor when the current ice thickness is greater than a preset value and the current ice change rate is not stable within a preset range; obtaining an image to be detected for the microwave sensor collected by an image acquisition device when the ice state of the power transmission line is determined to be an ice-water mixture state based on the meteorological data; and determining the final ice thickness of the power transmission line based on the image to be detected, thereby reducing the influence of the environment and the ice formation process and accurately determining the ice thickness of the power transmission line.

The invention relates to the technical field of power transmission line galloping icing detection, and particularly provides a power transmission line galloping icing detection method and system, and the method comprises the steps: collecting an image of a power transmission line under the condition that the temperature data and humidity data of an environment where the power transmission line is located reach preset thresholds; determining the icing thickness based on the ice layer reflection intensity feature and the edge thickness feature of the image; under the condition that the icing thickness reaches a preset threshold value, calculating the wire swing amplitude of the power transmission line based on an optical flow method; generating a three-dimensional track thermodynamic diagram based on the coordinate data of the power transmission line under the condition that the lead swing amplitude reaches a galloping judgment condition, the galloping judgment condition being determined according to the lead diameter of the power transmission line; and determining a detection result of power transmission line galloping icing based on the icing thickness and the three-dimensional track thermodynamic diagram. The problem of insufficient detection accuracy of a power transmission line detection system in the prior art is solved.

The invention relates to a power transmission line icing thickness dynamic prediction method based on a time sequence, and the method comprises the steps: collecting time sequence data, carrying out the preprocessing, and dividing the preprocessed data into a training set and a test set; inputting the training set into an LSTM neural network model for training; and inputting meteorological data and power transmission line data collected in real time into the trained model to obtain a prediction result, comparing the prediction result with a preset safety threshold, and when the predicted icing thickness exceeds the safety threshold, triggering an early warning mechanism. According to the invention, the relation between the meteorological change and the icing thickness is captured in a data driving mode, efficient dynamic prediction is realized, and a scientific basis is provided for anti-icing and deicing work of a power transmission line; the LSTM neural network model can efficiently capture time sequence dependence of data and provide accurate ice layer accumulation prediction, and an early warning mechanism can help a power operator to take anti-icing and deicing measures as soon as possible, so that damage to the power transmission line caused by freezing disasters is effectively reduced.

This application relates to the field of ice thickness measurement technology, specifically disclosing an ice thickness measurement device and method that supports both internal and external ice melting. By incorporating an adaptive ice threshold calibration module into the ice thickness measurement device, the device can adaptively calibrate the ice threshold when water quality changes, thereby improving the accuracy of identifying frozen areas and providing more accurate data support for ice thickness measurement and determination. This dynamic adjustment and calibration of the ice threshold ensures that ice thickness measurement results more accurately reflect the actual ice layer conditions, avoiding misjudgments due to water quality changes and maintaining high reliability in conductivity detection.

The application discloses a kind of ice thickness measurement method and device based on visual perception of ice storage coil, and the method comprises: setting annular or fan ring-shaped calibration disc on ice storage coil.The calibration disc is provided with multiple different color stripe regions arranged concentrically and along radial direction.Judge whether each stripe region is completely covered by ice layer according to the brightness change of calibration disc covered by ice layer in image, and each stripe region is divided into completely covered interval, partially covered interval and uncovered interval.For partially covered interval, the ice layer covering ratio of partially covered interval is obtained, and thus the ice layer thickness is obtained.The application provides the accuracy of ice thickness detection by stage ice thickness analysis, specifically, the ice layer completely covered by ice layer is determined by using the segmentation and brightness of different color stripe regions, and then for the partially covered stripe region, the comprehensive edge strength of integrated gradient edge strength and phase consistency edge strength is used for coverage ratio calculation.

The invention discloses a power transmission line icing thickness prediction method based on multi-modal sequence decomposition and BiLSTM network optimization. The method comprises the following steps: obtaining the icing thickness and meteorological data of a power transmission line; carrying out correlation analysis on the meteorological data, and screening out the meteorological data with strong correlation with the icing thickness as prediction model input data; decomposing the icing thickness sequence into a plurality of modal subsequences by using VMD; using an SBOA optimization algorithm to optimize the BiLSTM network parameters; constructing a BiLSTM model for each modal sub-sequence by using the optimal network parameters, and performing component prediction on each modal sub-sequence in combination with key meteorological data; and carrying out superposition reconstruction on the prediction result of each modal component to obtain an icing thickness prediction result. The prediction method can effectively solve the problem of low prediction precision of the icing thickness caused by strong nonlinearity, large volatility and the like of icing data.

The invention discloses a quantitative prediction method for an icing load of a power transmission line, and the method comprises the following steps: collecting and fusing multi-source meteorological data: employing a dual-polarization radar to invert the particle size distribution of liquid drops through differential reflectivity, calculating the content of supercooled water through a differential phase, and obtaining an atmosphere liquid water path and a vertical temperature profile; according to the measured wind speed, wind direction and wind shear index, an environment parameter field is constructed, and icing early warning is triggered; conducting wire state parameter real-time sensing: monitoring conducting wire three-axis amplitude and galloping frequency, obtaining conducting wire surface temperature gradient, quantifying damping effect of conducting wire galloping on collision efficiency and providing boundary conditions for a thermodynamic equation; mixed phase state dynamic discrimination: constructing a phase state discrimination matrix based on a combination rule of a temperature interval and droplet particle size distribution; dynamic collision efficiency correction: calculating the dynamic collision efficiency by adopting an unsteady state collision formula; thermodynamics-fluid mechanics coupling calculation is carried out; and ice coating load accumulation and output: calculating the ice coating thickness, mass and mechanical load.