Icing detection method and system based on tension and tilt angle sensors

Abstract

An icing detection method based on tension and tilt angle sensors. Two kinds of sensor data are comprehensively utilized, cross validation and mutual compensation are realized, and the precision of an icing monitoring result is improved; compared with a single sensor, data fusion of a multi-source heterogeneous sensor improves the robustness and the anti-interference ability of ice volume assessment, and improves the reliability of icing detection; an uncertainty analysis model for icing thickness is established, a confidence interval of a monitoring result is given, and more sufficient reference information is provided for related decisions; by setting a scientific and reasonable monitoring and early-warning mechanism, intelligent monitoring and early-warning of an icing condition are realized, and the intelligent level of the technology is improved; and by establishing an icing monitoring model, the icing condition of wires can be accurately predicted, and the early-warning and monitoring capabilities are improved to ensure the safe operation of a power grid. Also disclosed are an icing detection system based on tension and tilt angle sensors, a computer device and a computer-readable storage medium.

Description

Ice detection method and system based on tension and tilt sensors Technical Field

[0001] The present invention relates to the technical field of ice cover monitoring, and in particular to an ice cover detection method and system based on tension and tilt sensors. Background Art

[0002] Ice accumulation on transmission lines can cause line breakage and tower collapse, seriously threatening the safe operation of power grids. Therefore, the development of conductor icing prediction models has become a hot topic both domestically and internationally, with some theoretical progress already achieved. However, existing prediction models suffer from several issues, including neglecting the uneven loading effects of tension insulator strings and failing to account for the increased combined load caused by horizontal wind forces. Furthermore, the current lack of effective experimental validation of these prediction models has cast doubt on their accuracy.

[0003] Summary of the Invention

[0004] The present invention is proposed in view of the fact that the existing prediction models ignore the uneven load effect brought by the tension insulator strings and do not consider the problem of increased comprehensive load caused by horizontal wind force.

[0005] Therefore, the problem to be solved by the present invention is how to accurately predict the icing condition of the conductors and improve the early warning and monitoring capabilities to ensure the safe operation of the power grid.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, an embodiment of the present invention provides an ice detection method based on tension and inclination sensors, which includes measuring the axial stress of the conductor through a tension sensor to calculate the tension of the conductor, and denoising the tension; measuring the windage angle and tilt angle of the conductor through a inclination sensor to calculate the value of the conductor suspension angle; establishing an ice monitoring model based on the measurement data of the tension sensor and the inclination sensor; inputting real-time monitoring data into the ice monitoring model to obtain the current ice thickness of the conductor; when the ice thickness of the conductor exceeds the danger threshold, automatically triggering an alarm and notifying relevant personnel.

[0008] As a preferred solution of the ice detection method based on tension and tilt sensors of the present invention, the specific formula for the wire overhang angle value is as follows:

[0009] Among them, θ η represents the overhang angle in the converted windage plane, η represents the windage angle, and θ represents the tilt angle.

[0010] As a preferred solution of the ice detection method based on tension and tilt sensors of the present invention, the specific formula for denoising the tension is as follows:

[0011] Where σ represents the noise deviation, λ represents the number of wavelet coefficients, and n represents the tension.

[0012] As a preferred embodiment of the ice detection method based on tension and tilt sensors of the present invention, establishing an ice monitoring model includes the following steps: collecting and processing measurement data of the tension sensor and the tilt sensor, as well as the cross-sectional area A of the wire; verifying and judging the influencing factors, and calculating the ice weight load γ using the processed measurement data. i To describe the ice load; according to the conductor cross-sectional area A and ice weight load γ i Calculate the gravity Q of the icicle per unit length under the ice density ice ; Use the unit length of the icicle gravity Q ice Calculate the ice thickness b.

[0013] As a preferred embodiment of the ice accumulation detection method based on tension and inclination sensors described in the present invention, the verification and judgment of influencing factors include the following: verifying the data collected by the tension sensor and the inclination sensor, and comparing them with the set normal range. If the data exceeds the normal range, the data are marked as abnormal data and processed or filtered out; if the data is within the normal range, calibration is performed or data is directly collected; the influencing factors are detected, the wind speed is detected, and if it exceeds the maximum allowable wind speed designed for the conductor, the ice weight load calculation is suspended; the air temperature is detected, and if it is above the freezing point, the ice weight load calculation is suspended; when calculating the ice weight load, the measured data is compared with the data from the weather station. If the calculation result is obviously inconsistent with the actual weather conditions, the calculation process is re-checked; when the wind speed and air temperature conditions permit, the ice weight load calculation process is entered.

[0014] As a preferred solution of the ice detection method based on tension and tilt sensors of the present invention, the ice weight load γ is calculated. i The specific formula is as follows:

[0015] Among them, sinθ η and cosθ η represents the value of the wire hanging angle, λ represents the number of wavelet coefficients, σ B represents the axial stress of the conductor at the suspension point B, β represents the height difference angle formed by the height difference between the two towers, l represents the span, h represents the height difference between the suspension points, η represents the wind deflection angle, θ η represents the overhang angle in the converted windage plane, θ represents the tilt angle, γ c is the conductor load when there is no ice, γ fThe load on the conductor and ice when there is ice.

[0016] As a preferred solution of the ice detection method based on tension and tilt sensors of the present invention, the gravity of the icicle per unit length Q ice The specific formula is as follows: ice =Aγ i

[0017] Among them, γ i represents the ice weight specific load, and A represents the cross-sectional area of ​​the conductor;

[0018] The specific formula of ice thickness b is as follows:

[0019] Where d represents the conductor diameter, ρ0 represents the standard ice density of overhead lines in my country, and Q ice Indicates the gravity of the icicle per unit length.

[0020] In the second aspect, an embodiment of the present invention provides an ice detection system based on tension and inclination sensors, which includes a data processing module for measuring the axial stress of the conductor through a tension sensor to calculate the tension of the conductor and denoise the tension; a calculation module for measuring the windage angle and tilt angle of the conductor through a inclination sensor to calculate the value of the conductor suspension angle; a model building module for establishing an ice monitoring model based on the measurement data of the tension sensor and the inclination sensor; and an early warning module for automatically triggering an alarm and notifying relevant personnel when the ice thickness of the conductor exceeds a dangerous threshold.

[0021] In a third aspect, an embodiment of the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program instructions are executed by the processor, the steps of the ice detection method based on tension and tilt sensors as described in the first aspect of the present invention are implemented.

[0022] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program instructions are executed by a processor, the steps of the ice detection method based on tension and tilt sensors as described in the first aspect of the present invention are implemented.

[0023] The beneficial effects of the present invention are as follows: the present invention comprehensively utilizes data from two sensors to achieve cross-validation and mutual compensation, thereby improving the accuracy of ice monitoring results; compared with a single sensor, the data fusion of multi-source heterogeneous sensors enhances the robustness and anti-interference ability of ice volume assessment and improves the reliability of ice detection; an uncertainty analysis model for ice thickness is established, and a confidence interval for monitoring results is given, providing more sufficient reference information for relevant decision-making; by setting up a scientific and reasonable monitoring and early warning mechanism, intelligent monitoring and early warning of ice conditions are achieved, thereby improving the intelligence level of the technology; by establishing an ice monitoring model, the ice condition of the conductor can be accurately predicted, and the early warning and monitoring capabilities can be improved to ensure the safe operation of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort. Among them:

[0025] FIG1 is a flow chart of an ice detection method based on a tension and tilt sensor provided in Example 1;

[0026] FIG2 is an implementation diagram of the ice detection method based on tension and tilt sensors provided in Example 1;

[0027] FIG3 is a tension data fitting diagram of the ice detection method based on tension and tilt sensors provided in Example 2;

[0028] FIG4 is a diagram showing the inclination data fitting of the ice detection method based on the tension and inclination sensors provided in Example 2;

[0029] FIG5 is a fitting diagram of the relationship between tension and ice coverage in the ice coverage detection method based on tension and tilt sensors provided in Example 2;

[0030] FIG6 is a fitting diagram of the relationship between the inclination angle and ice coverage in the ice coverage detection method based on the tension and inclination sensor provided in Example 2. DETAILED DESCRIPTION

[0031] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0032] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0033] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive of other embodiments.

[0034] Example 1

[0035] 1 and 2 , which are the first embodiment of the present invention, provide an ice detection method and system based on tension and tilt sensors, including:

[0036] S1: The axial stress of the conductor is measured by a tension sensor to calculate the tension of the conductor and perform noise reduction on the tension.

[0037] Specifically, as shown in FIG2 , axial stress refers to the force for a fixed axial direction, and tension is calculated by measuring the x-axis axial stress and the y-axis axial stress.

[0038] Furthermore, the specific formula for denoising the tension is as follows:

[0039] Where σ represents the noise deviation, λ represents the number of wavelet coefficients, and n represents the tension.

[0040] Specifically, due to the measurement error of the tension sensor, the calculated ice thickness deviates from the theoretical value. This deviation is caused by the measurement drift error at the low end of the tension sensor's range. The relative error increases when the tension is small. In order to eliminate the influence of the tension measurement error on the ice thickness calculation, the wavelet transform denoising technology is used to process the tension signal.

[0041] It should be noted that the present invention adopts a fiber optic Bragg tension sensor as a key technology to improve the accuracy and reliability of conductor stress monitoring. The fiber optic Bragg tension sensor has the advantages of small size, light weight, no interference from electromagnetic fields, and high measurement accuracy. Its long life, reliable and stable characteristics are suitable for long-term use in field environments. In addition, the optical fiber itself does not conduct current, which ensures the electrical insulation performance of the sensor, and the optical fiber sensing network can achieve long-distance telemetry, making the acquisition of real-time monitoring data more convenient. By using wavelength division multiplexing technology to realize multiple tension measurement points on a single optical fiber, the accuracy and reliability of ice cover monitoring are further improved, making it possible to obtain more abundant first-hand data. Compared with resistive sensors, fiber optic Bragg tension sensors are more suitable for application on high-voltage conductors and can meet high-demand stress monitoring needs.

[0042] S2: The windage angle and tilt angle of the conductor are measured by the inclination sensor to calculate the conductor hanging angle value.

[0043] To ensure accurate measurement of the conductor's tilt and windage angles, the present invention preferably incorporates a high-precision, wide-range digital tilt sensor, capable of providing accurate tilt and windage data. The tilt sensor is mounted near the top of the conductor tower and secured with an insulating device to ensure that the sensor's angle changes with conductor deformation. This sensor collects tilt and windage data in real time and obtains accurate angle values ​​through digital signal processing techniques such as filtering, smoothing, and error compensation.

[0044] Specifically, the specific formula for the wire overhang angle value is as follows:

[0045] Among them, θ η represents the overhang angle in the converted windage plane, η represents the windage angle, and θ represents the tilt angle.

[0046] S3: Based on the measurement data of the tension sensor and the tilt sensor, an ice cover monitoring model is established.

[0047] Furthermore, the measurement data of the tension sensor and the tilt sensor, as well as the cross-sectional area A of the wire, are collected and processed; the ice weight load γ is calculated using the processed measurement data. i , to describe the ice load; according to the conductor cross-sectional area A and ice weight load γ i Calculate the gravity Q of the icicle per unit length under the ice density ice ; Use the unit length of the icicle gravity Q ice Calculate the ice thickness b.

[0048] It should be noted that the ice weight load γ i Before calculation, the following verification and judgment are required: Verify the data collected by the tension sensor and the inclination sensor: compare with the set normal range. If it exceeds the normal range, mark it as abnormal data and process or filter it out; if it is within the normal range, calibrate it (for sensors installed for the first time) or directly collect data (for previous sensors); detect the influencing factors: detect the wind speed. If it exceeds the maximum allowable wind speed of the conductor design, suspend the ice weight load calculation; detect the temperature. If it is above the freezing point, suspend the ice weight load calculation; when calculating the ice weight load, compare the measured data with the data from the weather station. If the calculation result is obviously inconsistent with the actual meteorological conditions, re-check the calculation process; when the wind speed and temperature conditions permit, enter the ice weight load calculation process.

[0049] Preferably, ice weight specific load γ i The specific formula is as follows:

[0050] Among them, sinθ η and cosθ η represents the value of the wire hanging angle, λ represents the number of wavelet coefficients, σ B represents the axial stress of the conductor at the suspension point B, σ A represents the axial stress of the conductor at the suspension point A, β represents the height difference angle formed by the height difference between the two towers, l represents the span, h represents the height difference between the suspension points, η represents the wind deflection angle, γ c is the conductor load when there is no ice, γ f is the load of the conductor and ice when there is ice, θ η Represents the overhang angle in the converted windage plane.

[0051] Furthermore, the unit length of the icicle gravity Q ice The specific formula is as follows: ice =Aγ i

[0052] Among them, γ i represents the ice weight specific load, and A represents the cross-sectional area of ​​the conductor;

[0053] Furthermore, the specific formula for ice thickness b is as follows:

[0054] Where d represents the conductor diameter, ρ0 represents the standard ice density of overhead lines in my country, and Q ice Indicates the gravity of the icicle per unit length.

[0055] It should be noted that the ice cover monitoring model established based on tension sensors and inclination sensors has the following advantages: the data of the two sensors are comprehensively utilized for cross-validation to improve monitoring accuracy; the tension sensor directly measures the impact of ice load on the conductor, and the inclination sensor measures the deformation of the conductor, and the two verify each other; the inclination angle can compensate for the shortcomings of the tension sensor being affected by wind load, and the combination of the two can distinguish the influence of wind load. By establishing a standardized ice thickness calculation model, the output results are made more unified and reliable; compared with a single sensor, the fusion of multi-source heterogeneous sensor data can improve the reliability and robustness of ice volume assessment.

[0056] S4: Input the real-time monitoring data into the ice coverage monitoring model to obtain the current ice coverage thickness of the conductor and perform uncertainty analysis on the ice coverage thickness.

[0057] Preferably, since the calculation results in ice thickness monitoring are affected by many factors and have certain uncertainties, an uncertainty model is established to analyze the influence of various error sources on the results.

[0058] Specifically, various factors that may cause uncertainty in monitoring results, such as sensor errors, environmental noise, and model assumptions, are listed; a propagation law method is used to establish a quantitative impact model of each uncertainty source on the final result; the numerical size of each uncertainty source is quantified through equipment indicators and experimental statistical means; each uncertainty source is introduced into the model to calculate the comprehensive standard uncertainty of the final ice thickness result.

[0059] Furthermore, the confidence interval of the measurement results is calculated using the comprehensive standard uncertainty as a parameter; determine whether the confidence interval range meets the requirements. If it is too large, consider improvement measures to narrow the interval range, and give the monitoring results in the form of an interval as a reference for subsequent decision-making; repeat the above process continuously to reduce uncertainty and improve the availability of the confidence interval.

[0060] S5: When the confidence interval of ice thickness monitoring overlaps with the confidence interval corresponding to the preset danger threshold, an early warning is automatically triggered.

[0061] Furthermore, the danger threshold range is determined based on historical data and risk assessment, and the corresponding confidence interval is calculated taking into account its own uncertainty; through uncertainty analysis, the confidence interval of the monitored ice thickness is calculated and updated in real time; an algorithm is used to compare the upper and lower limits of the two confidence intervals to determine whether there is overlap; once the monitored confidence interval overlaps with the confidence interval corresponding to the danger threshold, an early warning is automatically triggered.

[0062] Specifically, warning lights, sounds, pop-up prompts, etc. are used to prompt the system to enter the warning state, and warning notifications are sent to responsible personnel via text messages, emails, etc. After receiving the warning, relevant personnel immediately check the situation and prepare to activate the plan; continuously monitor changes in confidence intervals, and update warning judgments to ensure that warnings are in place.

[0063] Furthermore, this embodiment also provides an ice detection system based on tension and inclination sensors, including a data processing module for measuring the axial stress of the conductor through a tension sensor to calculate the tension of the conductor and to denoise the tension; a calculation module for measuring the windage angle and tilt angle of the conductor through an inclination sensor to calculate the value of the conductor suspension angle; a model building module for establishing an ice monitoring model based on the measurement data of the tension sensor and the inclination sensor; and an early warning module for automatically triggering an alarm and notifying relevant personnel when the ice thickness of the conductor exceeds a dangerous threshold.

[0064] This embodiment also provides a computer device, which is suitable for the ice detection method based on tension and tilt sensors, including a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the ice detection method based on tension and tilt sensors proposed in the above embodiment.

[0065] The computer device may be a terminal, comprising a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device comprises a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner may be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a button, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse.

[0066] This embodiment also provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the following steps: measuring the axial stress of the conductor by a tension sensor to calculate the tension of the conductor, and denoising the tension; measuring the windage angle and tilt angle of the conductor by a tilt sensor to calculate the value of the conductor suspension angle; establishing an ice monitoring model based on the measurement data of the tension sensor and the tilt sensor; inputting real-time monitoring data into the ice monitoring model to obtain the current ice thickness of the conductor; and automatically triggering an alarm and notifying relevant personnel when the ice thickness of the conductor exceeds a danger threshold.

[0067] In summary, the present invention comprehensively utilizes data from two types of sensors to achieve cross-validation and mutual compensation, thereby improving the accuracy of ice monitoring results. Compared with a single sensor, the data fusion of multi-source heterogeneous sensors enhances the robustness and anti-interference ability of ice volume assessment and improves the reliability of ice detection. An uncertainty analysis model for ice thickness is established, and a confidence interval for monitoring results is given, providing more sufficient reference information for relevant decision-making. By setting up a scientific and reasonable monitoring and early warning mechanism, intelligent monitoring and early warning of ice conditions are realized, thereby improving the intelligence level of the technology. By establishing an ice monitoring model, the ice condition of the conductor can be accurately predicted, and the early warning and monitoring capabilities can be improved to ensure the safe operation of the power grid.

[0068] Example 2

[0069] 3 to 6 , a second embodiment of the present invention is shown. This embodiment provides an ice detection method based on tension and tilt sensors. To verify the beneficial effects of the present invention, economic benefit calculations and simulation experiments are used for scientific demonstration.

[0070] Specifically, the analysis results in Table 1 show that there is a certain error between the tension sensor's measured value and the actual tension value. The ice thickness corresponding to the actual tension value is theoretically calculated, while the actual ice thickness is derived from the sensor's measurement. The maximum difference between the two values ​​is 0.2 mm, resulting in a maximum relative error of 2.6%. This relative error is particularly significant when the tension is low. To eliminate this error, tension denoising is used.

[0071] Table 1 Influence of tension sensor measurement error on ice thickness

[0072] Preferably, the fiber Bragg tensile sensor is connected to the universal tensile machine with hardware, and the fiber Bragg grating sensor is connected to the demodulator via an FC jumper, and the demodulator is connected to the PC via a USB data cable.

[0073] Specifically, the tensile sensor was preloaded, and a universal tensile testing machine was used to apply a load, gradually increasing from 0kN to 40kN, and then gradually decreasing to 0kN; the wavelength of the sensor when it was in an unloaded state was recorded (that is, the wavelength value of the sensor was recorded when there was no load); the detection points of the tensile sensor were set, and when the universal tensile testing machine applied a load of 0kN, 10kN, 20kN, 30kN, and 40kN, they were maintained for 3 minutes respectively, and the value of the wavelength of the sensor after it stabilized was observed; the load of the universal tensile testing machine on the sensor was gradually reduced, and when the load was reduced to the detection points of 30kN, 20kN, 10kN and 0kN, it was also maintained for 3 minutes, and the value of the central wavelength of the sensor was observed. The experimental results are shown in Table 2. The results of the six experiments were linearly fitted using MATLAB software, as shown in Figure 3.

[0074] Table 2 Tensile sensor experimental results

[0075] After obtaining the noise-reduced tension value, the tilt angle was measured. The wavelength of the grating was recorded for each tilt angle from 0° to 5.2° during the descent and from 0° to 5.2° during the ascent, and each monitoring point was maintained for 5 minutes. A fiber Bragg grating sensor can only measure tilt in one dimension. Substituting the wavelengths of the two gratings into the formula can calculate the tilt angle.

[0076] It should be noted that the time for each monitoring point was maintained for 5 minutes in the experiment, and the experimental data are shown in Table 3.

[0077] Table 3 Tilt sensor experimental data

[0078] Furthermore, the results of the three experiments were plotted using MATLAB software, with the experimental results shown in Figure 4. Combining the tension fitting graph and the inclination fitting graph allows for ice detection, as shown in Figures 5 and 6. The error between the detected data and the calculated data is less than 0.3%.

[0079] It should be noted that the upper part of Figure 5 shows the trend of tension change, the lower part shows the trend of ice thickness change, the short wavy lines in Figure 6 show the trend of ice thickness change, and the thick lines show the trend of inclination change.

[0080] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. An ice detection method based on tension and tilt sensors, characterized in that: include, The axial stress of the conductor is measured by a tension sensor to calculate the tension of the conductor, and the tension is de-noised; The wind deflection angle and tilt angle of the conductor are measured by the inclination sensor to calculate the conductor hanging angle value; Based on the measurement data of the tension sensor and the tilt sensor, an ice cover monitoring model is established; Input the real-time monitoring data into the ice monitoring model to obtain the current ice thickness of the conductor and perform uncertainty analysis on the ice thickness; When the confidence interval of ice thickness monitoring overlaps with the confidence interval corresponding to the preset danger threshold, an early warning is automatically triggered.

2. The ice detection method based on tension and tilt sensors according to claim 1, characterized in that: The specific formula for calculating the wire hanging angle value is as follows: Among them, θ η represents the overhang angle in the converted windage plane, η represents the windage angle, and θ represents the tilt angle.

3. The ice detection method based on tension and tilt sensors according to claim 1, characterized in that: The specific formula for denoising the tension is as follows: Among them, σ represents the noise deviation, λ represents the number of wavelet coefficients, and n represents the tension.

4. The ice detection method based on tension and tilt sensors according to claim 1, characterized in that: The establishment of the ice coverage monitoring model comprises the following steps: Collect and process the measurement data of the tension sensor and the inclination sensor, as well as the cross-sectional area A of the wire; Verify and judge the influencing factors, and use the processed measurement data to calculate the ice weight load γ i To describe the ice load; According to the conductor cross-sectional area A and ice weight specific load γ i Calculate the weight Q of the ice column per unit length under the ice density ice ; Using the unit length of the ice column gravity Q ice Calculate the ice thickness b.

5. The ice detection method based on tension and tilt sensors according to claim 4, characterized in that: The verification and judgment of the influencing factors include the following contents: Verify the data collected by the tension sensor and the tilt sensor. If the data exceeds the normal range, it will be marked as abnormal data and treatment or filtering; If it is within the normal range, perform calibration or directly collect data; To test the influencing factors, Check the wind speed. If it exceeds the maximum allowable wind speed designed for the conductor, the ice load calculation will be suspended. Check the air temperature, if it is above freezing point, suspend the ice load calculation; When calculating ice weight load, Compare the measured data with the data from the weather station. If the calculated results are obviously inconsistent with the actual weather conditions, recheck the calculation process; When wind speed and air temperature conditions permit, enter the ice weight load calculation process.

6. The ice detection method based on tension and tilt sensors according to claim 4, characterized in that: The calculation of ice weight specific load γ i The specific formula is as follows: Among them, sinθ η and cosθ η represents the wire hanging angle value, λ represents the number of wavelet coefficients, σ B represents the axial stress of the conductor at the suspension point B, β represents the height difference angle formed by the height difference between the two towers, l represents the span, h represents the height difference between the suspension points, η represents the wind deviation angle, θ η represents the overhang angle in the converted windage plane, θ represents the tilt angle, γ c is the conductor load when there is no ice, γ f The load on the conductor and ice when there is ice.

7. The ice detection method based on tension and tilt sensors according to claim 4, characterized in that: The unit length of the ice column is gravity Q ice The specific formula is as follows: ice =Aγ i Among them, γ i represents the ice weight specific load, A represents the cross-sectional area of ​​the conductor; The specific formula of the ice thickness b is as follows: Where d represents the conductor diameter, ρ0 represents the standard ice density of overhead lines in my country, and Q ice Indicates the gravity of the icicle per unit length.

8. An ice detection system based on a tension and tilt sensor, based on the ice detection method based on a tension and tilt sensor according to any one of claims 1 to 7, characterized in that: Also includes, A data processing module, used for measuring the axial stress of the conductor through a tension sensor to calculate the tension of the conductor, and performing a denoising process on the tension; A calculation module is used to measure the windage angle and tilt angle of the conductor through a tilt sensor to calculate the value of the conductor hanging angle; A model building module is used to build an ice monitoring model based on the measurement data of the tension sensor and the tilt sensor; The early warning module is used to automatically trigger an alarm and notify relevant personnel when the ice thickness of the wire exceeds the danger threshold.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the ice detection method based on tension and tilt sensors according to any one of claims 1 to 7 are implemented.

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

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