Power transmission line tower attitude monitoring method and system based on multi-dimensional sensing

Abstract

The invention belongs to the technical field of attitude monitoring, and particularly relates to a power transmission line tower attitude monitoring method and system based on multi-dimensional sensing, and the method comprises the steps: collecting original inclination angle time sequence data and synchronous environment state data of a power transmission tower, and constructing a time-varying environment turbulence energy index through a sliding window mechanism; based on the index, utilizing a hyperbolic tangent function to construct nonlinear adaptive observation impedance; constructing a quasi-static equilibrium evolution model containing adaptive observation impedance, and iteratively updating a truth value settlement vector of the tower in combination with a direction consistency factor; and calculating the comprehensive gradient based on the truth value settlement vector and triggering a multi-stage early warning mechanism. According to the method, elastic deformation interference caused by wind vibration and thermal drift is effectively eliminated through noise quantification of a physical level and a nonlinear intelligent gating mechanism, and accurate extraction and zero false alarm monitoring of the micro plastic settlement trend of the tower under the complex meteorological condition of the goaf are achieved.

Description

Technical Field

[0001] This invention relates to the field of attitude monitoring technology. More specifically, this invention relates to a method and system for monitoring the attitude of transmission line towers based on multi-dimensional sensing. Background Technology

[0002] In the field of geological disaster monitoring for power transmission lines, especially in areas with dense mining subsidence, tower tilt monitoring is the core means of preventing tower collapse accidents; and as a tall, flexible metal structure, the attitude data of power transmission towers is greatly affected by environmental loads.

[0003] Existing technologies typically utilize microelectromechanical systems (MEMS) tilt sensors installed on towers to acquire raw angle data, and then use moving average filtering, Kalman filtering, or setting a fixed threshold to determine whether the tower has settled.

[0004] However, the aforementioned existing technologies have significant limitations when facing the complex meteorological environment of goaf areas. On the one hand, goaf areas are often accompanied by complex terrain and wind fields. Strong winds can cause high-frequency elastic swaying of towers, i.e., wind-induced vibration, while drastic diurnal temperature differences can cause low-frequency periodic displacement of tower materials due to thermal expansion and contraction, i.e., thermal drift. Both of these deformations are recoverable elastic deformations, which often numerically mask the extremely small but fatal irreversible plastic settlement of the goaf foundation. On the other hand, existing linear filtering algorithms assume that noise follows a Gaussian distribution, which cannot cope with the non-zero mean long-tailed noise caused by continuous gusts of wind, nor can they automatically adapt to sudden meteorological conditions. This leads to existing technologies either generating a large number of false alarms due to wind-induced vibration or failing to report early, minor settlement trends due to over-smoothing.

[0005] Therefore, existing technologies have the technical problem of being unable to accurately decouple and extract the true irreversible settlement trend of towers under non-stationary environmental load disturbances. Summary of the Invention

[0006] To address the technical problem that existing technologies cannot accurately decouple and extract the true irreversible settlement trend of towers under non-stationary environmental load disturbances, the present invention provides solutions in the following aspects.

[0007] In a first aspect, the present invention provides a method for monitoring the attitude of transmission line towers based on multi-dimensional sensing, comprising: collecting time-series data of the original tilt angle of the transmission line tower and synchronous environmental state data; preprocessing the data using a sliding window mechanism to construct a time-varying environmental turbulence energy index to quantify the disturbance intensity of environmental load on the tower from a dynamic perspective; constructing a nonlinear adaptive observation impedance based on the environmental turbulence energy index using a hyperbolic tangent function; constructing a quasi-static equilibrium evolution model including the adaptive observation impedance, and iteratively updating the true settlement vector of the tower by combining a direction consistency factor; the quasi-static equilibrium evolution model uses the reciprocal of the adaptive observation impedance as the dynamic update step size, and uses a direction consistency factor reflecting the cosine value of the angle between the current measurement increment direction and the historical settlement trend direction to weight the update amplitude in order to shield against reciprocating oscillation interference; calculating the comprehensive tilt angle based on the true settlement vector, and triggering a corresponding multi-level early warning mechanism according to a preset geological hazard classification standard for goaf areas.

[0008] This invention constructs an environmental turbulence energy index that includes kinetic and thermal energy terms, which, unlike traditional frequency domain filtering techniques, quantifies the noise-inducing ability of the environment on towers in real time from a physical perspective. It can accurately identify the interfered and clean intervals in the data, providing a precise physical basis for subsequent differentiated processing. Combined with an adaptive observation impedance model based on the hyperbolic tangent function, an intelligent gating mechanism is established that locks out in harsh environments and allows passage in stable environments. Utilizing the high virtual inertia generated by nonlinear impedance during strong winds or drastic temperature changes, it effectively resists long-tailed noise interference from non-zero mean, solving the problem of false trend reports easily generated by traditional methods under continuous strong winds. At the same time, by using a quasi-static equilibrium evolution model, signal processing is transformed into a constrained physical evolution process. By dynamically adjusting the evolution step size and introducing a directional consistency factor, it can completely remove the large-amplitude elastic wind vibration interference and reciprocating swaying while accurately preserving the extremely small geological subsidence trend, achieving zero false alarm and accurate capture of tower micro-subsidence under complex meteorological conditions in goaf areas.

[0009] Preferably, the formula for calculating the environmental turbulence energy index is: In the formula, Indicates time Environmental turbulence energy index; Indicates the length of the sliding time window; This represents any point in the sliding time window; Indicates time The original tilt angle vector; This represents the derivative of the original tilt angle vector with respect to time. Represents the Euclidean norm operation for vectors; Indicates time Ambient temperature; Indicates time Ambient temperature; Indicates the reference temperature constant; This represents the natural exponential function.

[0010] This invention characterizes wind vibration energy by calculating the root mean square of the derivative of the original tilt angle vector with respect to time within a sliding window, and characterizes thermal energy impact by calculating the exponential function of the rate of temperature change. It unifies heterogeneous mechanical vibration and thermal stress deformation into a scalar environmental turbulence energy index. This construction method can keenly capture moments when the environment becomes noisy, providing a physical quantitative basis for subsequent judgment on whether to increase system damping, and ensuring that the system is effectively updated only in the range of clean data.

[0011] Preferably, the formula for calculating the adaptive observation impedance is: In the formula, Indicates time Adaptive observation impedance; The reference impedance is obtained through actual measurement and calculation, and corresponds to the basic sensitivity of the system under calm weather conditions. Indicates the impedance gain coefficient; Represents the hyperbolic tangent function; Indicates time Environmental turbulence energy index; This represents the potential energy threshold.

[0012] This invention utilizes the saturation characteristics of the hyperbolic tangent function and the nonlinear characteristics of the power function to construct an adaptive observation impedance. It also constructs a soft threshold gating mechanism, which causes the system impedance to rise exponentially and rapidly to saturation when the environmental turbulence energy index exceeds the potential energy threshold. This constructs a high-inertia characteristic of the physical system under high-frequency disturbances, thereby effectively resisting the interference of long-tailed noise with non-zero mean and avoiding the introduction of false settlement due to incorrect acceptance of measurement data during periods of continuous strong winds or drastic temperature changes.

[0013] Preferably, the formula for calculating the true settlement vector is: In the formula, Indicates time The estimated ground truth sedimentation vector after denoising; Indicates time The estimated true settlement vector; Indicates time The original tilt angle vector; Indicates time Adaptive observation impedance; It represents the dimension conversion factor, the value of which is equal to the unit impedance value; This indicates that the step size is updated dynamically. Indicates time The directional consistency factor.

[0014] This invention constructs a quasi-static equilibrium evolution model, which models the extraction process of the true settlement vector as the force evolution process of a physical entity. The reciprocal of the adaptive observation impedance is used as the dynamic update step size. When encountering strong winds that cause the impedance to be extremely high, the update step size approaches zero, and the system refuses to follow the changes in wind vibration signals. However, when the environment is stable and the impedance is small, the system can quickly approach the measured value, thereby achieving physical shielding of high-frequency reciprocating signals and lossless passage of low-frequency unidirectional trends.

[0015] Preferably, the direction consistency factor is obtained by performing a dot product operation between the measurement increment vector at the current moment and the historical subsidence trend vector calculated based on a long time window, and obtaining the cosine value of the angle between the two as the direction consistency factor.

[0016] This invention uses the cosine of the angle between the current measurement increment vector and the historical subsidence trend vector as a directional consistency factor, and forcibly stipulates that updates are suppressed when the directional consistency factor is negative. This mechanism introduces the continuity constraint of physical motion, which can identify and eliminate transient disturbances that, although large in magnitude, are opposite to the long-term subsidence trend. This further ensures that the extracted true subsidence vector only reflects continuous plastic geological deformation.

[0017] Preferably, the acquisition of the original tilt angle time-series data of the transmission tower and the synchronous environmental status data includes: acquiring the original tilt angle vector containing the tilt angle components along the line direction and the tilt angle components across the line direction at real time at a set sampling rate using a dual-axis tilt sensor installed on the crossarm of the transmission tower; and acquiring the synchronous tower surface ambient temperature using a temperature probe integrated inside the dual-axis tilt sensor.

[0018] Preferably, calculating the overall tilt angle based on the true settlement vector includes: calculating the modulus of the true settlement vector; calculating the tangent value of the modulus using the tangent function, and multiplying the tangent value by a conversion factor from meters to millimeters to obtain the overall tilt angle of the tower in millimeters per meter.

[0019] Preferably, the triggering of the corresponding multi-level early warning mechanism includes: if the overall tilt exceeds the first-level threshold, triggering a blue warning and automatically encrypting the sampling frequency; if the overall tilt exceeds the second-level threshold, triggering a yellow warning and sending a trend prediction report; if the overall tilt exceeds the third-level threshold, triggering a red alarm and linking the video surveillance system to capture on-site footage.

[0020] This invention establishes a multi-level early warning mechanism, which triggers response actions such as encrypted sampling, trend reporting, and video capture based on the magnitude of the overall tilt. This enables on-demand allocation of monitoring resources and hierarchical risk management. It can capture minute changes through encrypted data in the early stages of a risk and eliminate false alarms through visual confirmation in critical moments, thereby improving the response speed and decision-making accuracy of power grid operation and maintenance.

[0021] Preferably, the first-level threshold is less than the second-level threshold, and the second-level threshold is less than the third-level threshold.

[0022] In a second aspect, the present invention provides a transmission line tower attitude monitoring system based on multidimensional sensing, comprising a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the aforementioned transmission line tower attitude monitoring method based on multidimensional sensing is implemented.

[0023] By adopting the above technical solution, a computer program is generated from the above-mentioned method for monitoring the attitude of transmission line towers based on multi-dimensional sensing, and stored in a memory so that it can be loaded and executed by a processor. In this way, a terminal device can be made based on the memory and the processor for convenient use.

[0024] The beneficial effects of this invention are as follows:

[0025] (1) This invention differs from traditional frequency domain filtering techniques by using a sliding window mechanism to construct an environmental turbulence energy index that includes wind vibration energy and thermal shock energy terms. This index can quantify the noise-causing ability of environmental loads on towers in real time from a dynamic perspective, and unify the heterogeneous mechanical vibration and thermal stress deformation into a scalar physical index, so that the system can accurately identify the disturbed interval and the clean interval in the data, providing a physical quantitative basis for subsequent differential processing, thereby effectively solving the technical problem that traditional methods cannot distinguish between environmental noise and actual settlement.

[0026] (2) Based on the environmental turbulence energy index, this invention utilizes the saturation characteristics of the hyperbolic tangent function and the nonlinear characteristics of the power function to construct an adaptive observation impedance, and establishes an intelligent gating mechanism that locks out when the environment is harsh and allows passage when the environment is stable. This mechanism utilizes the nonlinear impedance to generate a large virtual inertia during strong winds or drastic temperature changes, which can effectively resist the interference of long-tailed noise with non-zero mean, and avoid the introduction of false settlement due to incorrect acceptance of measurement data during continuous strong winds or drastic day-night temperature differences, thus ensuring the robustness of the system under all-weather meteorological conditions.

[0027] (3) The present invention constructs a quasi-static equilibrium evolution model containing adaptive observation impedance and uses the direction consistency factor as a constraint condition to transform the extraction process of the true value trend into a restricted physical evolution process. By using the reciprocal of the impedance to dynamically adjust the evolution step size and forcibly suppressing updates that are opposite to the historical trend, the system can completely remove the huge elastic wind vibration interference and reciprocating sway while accurately retaining the extremely small and continuous plastic geological settlement trend, thus achieving zero false alarm and accurate capture of tower micro-settlement under complex environmental loads in the goaf area.

[0028] (4) The present invention ensures the high consistency of tilt angle data and ambient temperature data in time and space through synchronous acquisition at the hardware level, eliminating the error of correlation analysis; at the same time, by calculating the comprehensive tilt degree and matching the multi-level early warning mechanism, the system can automatically trigger encrypted sampling, trend report or video linkage according to the severity of settlement, realizing the on-demand allocation of monitoring resources and the hierarchical management of risks, significantly improving the response speed and decision accuracy of power grid operation and maintenance. Attached Figure Description

[0029] Figure 1 This is a flowchart illustrating a method for monitoring the attitude of transmission line towers based on multidimensional sensing according to the present invention. Figure 2 This is a schematic diagram illustrating the original tilt angle timing data; Figure 3 This is a schematic diagram illustrating the time-varying nature of environmental turbulence energy indices; Figure 4 This is a schematic diagram illustrating the dynamic adjustment of adaptive observation impedance; Figure 5 This is a schematic diagram illustrating the comparison of the true value trend extraction effect of transmission towers. Detailed Implementation

[0030] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0031] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0032] This invention discloses a method for monitoring the attitude of transmission line towers based on multi-dimensional sensing, referring to... Figure 1 This includes steps S1-S4: S1. Collect the original tilt angle time series data of the transmission tower and the synchronous environmental state data, and use the sliding window mechanism to preprocess the data to construct the time-varying environmental turbulence energy index.

[0033] It should be noted that since the instantaneous attitude of the transmission tower is a physical superposition of foundation settlement, wind load elastic bending and thermal stress deformation, directly using the raw data to make trend judgments will lead to misjudgment. Therefore, this embodiment first needs to quantify the disturbance capability of the current environment on the tower from a dynamic perspective. By calculating the environmental turbulence energy index, the high noise interval in the data is identified, providing a quantitative basis for subsequent differentiated processing.

[0034] Specifically, a dual-axis tilt sensor installed on the crossarm of the transmission tower collects real-time data at a set sampling rate. The original tilt angle vector The unit is degrees; in this embodiment, the sampling rate is set to 20Hz. It includes tilt angle components along the track direction and tilt angle components across the track direction; simultaneously, it obtains the synchronous ambient temperature of the tower surface through a temperature probe integrated inside the sensor. .

[0035] For example, Figure 2 The diagram shows the original tilt angle time series data after sensor acquisition and preprocessing. The 300 to 500 seconds correspond to the small settlement zone, and the 600 to 900 seconds correspond to the strong wind interference zone. Under strong wind interference, the original data contains high-frequency wind vibration and low-frequency oscillation noise with drastic amplitude, making it difficult to use directly for settlement trend judgment.

[0036] Furthermore, the collected data is input into the computing unit to construct a length of The sliding time window; in this embodiment, in order to effectively capture kinetic energy, the length of the sliding time window is... Coverage for at least 2-3 seconds; therefore, the length Set to 60 sampling points.

[0037] Furthermore, based on the sliding time window, the time is calculated. Environmental turbulence energy index The calculation process satisfies the following expression:

[0038] In the formula, Indicates time The environmental turbulence energy index is used to quantify the intensity of the disturbance of the environmental load on the tower attitude at the current moment. Indicates the length of the sliding time window; This represents any point in the sliding time window; Indicates time The original tilt angle vector; This represents the derivative of the original tilt angle vector with respect to time, i.e., the angular velocity vector of the tower's oscillation; Represents the Euclidean norm operation for vectors; Indicates time Ambient temperature; Indicates time Ambient temperature; Indicates the reference temperature constant; This represents the natural exponential function.

[0039] The first part, the root mean square term, calculates the energy of the tower's oscillation angular velocity within the window period. When wind speed increases, leading to more severe tower swaying, the angular velocity increases, causing this term to rise significantly, thus reflecting the magnitude of wind-induced vibration energy. The second part, the exponential term, calculates the rate of temperature change within the window period. When drastic temperature changes occur, the exponential function value increases rapidly, acting as a weighted amplification. When ambient wind speed increases or temperature changes abruptly... The value increases non-linearly; when the environment is stable, The value approaches zero.

[0040] For example, Figure 3 The diagram illustrates the time-varying nature of the environmental turbulence energy index, showing the curve of the environmental turbulence energy index changing over time in this embodiment. In the first half of the stable environmental period, the energy index value remains at a low level, below the potential energy threshold. In the second half of the storm interference period, due to the high-frequency wind vibration of the tower, the energy index value rises rapidly and significantly exceeds the potential energy threshold. The change of this index accurately reflects the degree of turbulence of the external environmental load, providing a physical basis for the subsequent adjustment of the adaptive observation impedance.

[0041] It should be noted that this embodiment maps heterogeneous wind vibration energy and thermal energy impact into a single scalar index, which can keenly capture moments when the environment becomes noisy, providing a unique input variable for subsequent steps to determine whether the filter impedance needs to be increased.

[0042] S2. Based on the environmental turbulence energy index, a nonlinear adaptive observation impedance is constructed using the hyperbolic tangent function to quantify the system's confidence in the current measurement value.

[0043] It should be noted that, in high-noise environments such as strong winds or drastic temperature changes, sensor readings contain a large number of elastic deformation components. If the update trend of the measured value is directly accepted, false settlement will be introduced. Therefore, this embodiment constructs an adaptive observation impedance and uses the characteristics of nonlinear functions to automatically increase the resistance to system updates when the environmental turbulence energy index increases, simulating the high inertia characteristics of the physical system under high-frequency disturbances, thereby shielding environmental noise.

[0044] Specifically, based on the calculated environmental turbulence energy index Calculate time Adaptive observation impedance The calculation process satisfies the following expression:

[0045] In the formula, Indicates time The adaptive observation impedance, which determines the degree to which the system accepts new measurement data at the current moment; The reference impedance is obtained through actual measurement and calculation, and corresponds to the basic sensitivity of the system under calm weather conditions. It is used as a zero-point reference for subsequent judgment of the degree of thermal drift. Indicates the impedance gain coefficient; Represents the hyperbolic tangent function; Indicates time Environmental turbulence energy index; This represents the potential energy threshold.

[0046] The method for obtaining the reference impedance is as follows: In a cold system environment, a control signal generator transmits a standard pulse signal with a carrier frequency equal to the system center frequency to the power amplifier, and simultaneously acquires time-domain voltage data and time-domain current data at the output of the power amplifier through a high-frequency sampling circuit; subsequently, a fast Fourier transform is performed on the acquired voltage and current data to extract the complex impedance at the fundamental frequency, which includes resistive and reactive components; the magnitude of this complex impedance is further calculated as the reference impedance magnitude, which characterizes the sum of the inductance and resistance of the coil in a cold state, and is stored as a physical reference for subsequently measuring changes in permeability.

[0047] in, The impedance gain coefficient controls the maximum impedance ratio of the system under extreme conditions. If this value is set too low, even in strong winds, the system's upper impedance limit will still be insufficient, causing the wind vibration signal of the tower to be incorrectly treated as a settlement trend, leading to false alarms. If this value is set too high, the system will enter a locked state under slight disturbances, unable to update readings for a long time, resulting in significant measurement lag. Based on the above analysis... The value range is [50, 200]; in this embodiment, Setting it to 100 can effectively shield against interference from level 10 gale-force winds while maintaining the ability to track hourly settlement trends; in other embodiments, implementers can set the impedance gain coefficient within the range of [50, 200] according to the actual implementation situation.

[0048] in, The potential energy threshold defines the critical energy point at which the environment transitions from steady to turbulent. If this value is set too small, the system will be overly sensitive, misinterpreting normal light breeze disturbances as strong turbulence, leading to an unnecessary decrease in the data update rate. If this value is set too large, the system will be less sensitive to severe weather, failing to promptly increase impedance, resulting in noise penetrating the filter. Based on the above analysis, The value range is [0.02, 0.1]; in this embodiment, The value is set to 0.05, which is the optimal segmentation point obtained after statistical analysis of historical typhoon day data; in other embodiments, implementers can set the potential energy threshold in the range of [0.02, 0.1] according to the actual implementation situation.

[0049] Among them, a soft threshold gating system was constructed using the nonlinear characteristics of the cubic power function, achieving smooth yet decisive impedance switching; a soft switch was constructed using the saturation characteristics of the hyperbolic tangent function and the nonlinearity of the power function: when Less than When the function value is extremely small, the impedance remains near the reference value; when Exceed At that time, the function value increases exponentially and quickly saturates; as the severity of the environment increases, Will from rapidly increased to .

[0050] For example, Figure 4 This diagram illustrates the dynamic adjustment of adaptive observation impedance in this embodiment, showing the curve of the adaptive observation impedance dynamically adjusting with the environmental turbulence energy index. When the environment is stable, the impedance value remains near the reference value, and the system is in low impedance mode, which can sensitively capture minute changes. When the environment is severely disturbed, the impedance value jumps exponentially, and the system automatically switches to high impedance mode, using huge virtual inertia to shield external noise interference.

[0051] It should be noted that this embodiment implements an adaptive adjustment mechanism that adapts to harsh environments (high resistance) and stable environments (low resistance), ensuring that the system only performs significant updates when the data is clean.

[0052] S3. Construct a quasi-static equilibrium evolution model that includes adaptive observation impedance, and iteratively update the true settlement vector of the tower by combining directional consistency constraints.

[0053] It should be noted that, since traditional mathematical filtering lacks physical constraints, it is easy to misjudge reciprocating wind vibration as unidirectional settlement. Therefore, this embodiment constructs a quasi-static equilibrium evolution model, models the extraction process of true value settlement as an evolution process constrained by impedance, and introduces a direction consistency factor, which forces that only when the tilt trend of the external input is continuous and the direction is stable can the constraint of high impedance be overcome and the true value be displaced, thereby eliminating the interference of reciprocating oscillation.

[0054] Specifically, the directional consistency factor is first calculated. Utilizing the moment The measured increment vector is multiplied by the historical settlement trend vector calculated based on a long time window, and the cosine of the angle between the two is obtained as the... Wherein, the time The measurement increment vector is equal to time. The original tilt angle vector Compared to the previous moment, i.e., the moment Estimated true settlement vector The difference, wherein the historical subsidence trend vector calculated based on a long time window is equal to the value at time [time]. Estimated true settlement vector With time Estimated true settlement vector The difference; if the magnitude of the historical trend vector approaches zero, then the default direction consistency factor is used. . The length of the long-term window is defined because geological subsidence is a slow variable, requiring measurements to be taken over minutes. Therefore, this embodiment sets the length accordingly. 1200 sampling points are used to calculate the historical trend vector.

[0055] Furthermore, the calculated adaptive observation impedance is used... The time step is calculated using a discrete quasi-static equilibrium evolution model. The true value of the settlement vector The calculation process satisfies the following expression:

[0056] In the formula, Indicates time The estimated ground truth sedimentation vector after denoising; Indicates time The estimated true settlement vector; Indicates time The original tilt angle vector; Indicates time Adaptive observation impedance; It represents the dimension conversion factor, the value of which is equal to the unit impedance value, and is used to eliminate the difference in physical dimensions; This represents the dimensionless dynamic update step size; Indicates time The directional consistency factor.

[0057] Among them, Viewed as a driving force, This is considered resistance; the update magnitude is determined by the ratio of driving force to resistance and is subject to the direction factor. Weighted; when encountering strong winds leading to At its maximum, the dynamic update step size approaches zero, making It remains almost unchanged, meaning the system refuses to follow wind vibrations; when the wind is calm... When the size is small, the dynamic update step size becomes larger, making Approaching rapidly At the same time, if A negative value, meaning the current direction of movement is opposite to the historical trend, will also inhibit updates.

[0058] It should be noted that this embodiment achieves physical shielding of high-frequency reciprocating signals and lossless passage of low-frequency unidirectional trends, enabling accurate reconstruction of the plastic settlement trajectory of the foundation from signals submerged in noise.

[0059] S4. Calculate the comprehensive tilt based on the true value settlement vector, and trigger the corresponding multi-level early warning mechanism according to the preset geological hazard classification standard for goaf areas.

[0060] It should be noted that since the true settlement vector extracted in step S3 is pure data after physical denoising, it accurately reflects the actual attitude of the tower. Therefore, this embodiment calculates the comprehensive tilt based on this vector and compares it with the geological disaster standard to achieve accurate business early warning.

[0061] Specifically, for the true settlement vector After unit conversion and using trigonometric relationships, the true settlement vector in degrees (°) is transformed into physical tilt in millimeters per meter (mm / m). The conversion formula is as follows:

[0062] In the formula, Indicates time The overall tilt of the tower; Indicates time The estimated ground truth sedimentation vector after denoising; This indicates taking the vector magnitude. It is the tangent function; This is the conversion factor from meters to millimeters.

[0063] Furthermore, Compare with the preset geological hazard classification threshold for goaf areas: If Exceeding the first-level threshold triggers a blue alert, and the system automatically encrypts the sampling frequency; if If the threshold is exceeded (level 2), a yellow alert is triggered, and a trend prediction report is sent to the operations and maintenance center; if If the threshold exceeds the third level, a red alarm is triggered, and the video surveillance system is activated to capture images of the scene and guide the emergency repair personnel to intervene. The first level threshold is less than the second level threshold, and the second level threshold is less than the third level threshold. In this embodiment, the first level threshold, the second level threshold, and the third level threshold are set to 3mm / m, 5mm / m, and 10mm / m, respectively.

[0064] For example, Figure 5 This diagram illustrates the comparison of the results of extracting the true trend of power transmission tower data. It shows the results of different techniques in a complex simulation scenario involving minor foundation settlement and extreme storm interference. Using the physical true value of foundation settlement as an ideal reference, the trend extraction results obtained using existing techniques (such as moving average filtering) are affected by non-zero mean noise in the storm range, resulting in significant false trend fluctuations that exceed the secondary threshold and cause false alarms. The trend extraction results obtained using the method in this embodiment closely follow the physical true value in the minor settlement range, demonstrating high sensitivity. In the storm interference range, it maintains a stable and locked state, unaffected by environmental noise, and is far below the primary threshold, demonstrating excellent anti-interference capability.

[0065] This invention also discloses a transmission line tower attitude monitoring system based on multidimensional sensing, including a processor and a memory. The memory stores computer program instructions, which, when executed by the processor, implement a transmission line tower attitude monitoring method based on multidimensional sensing according to the present invention.

[0066] The system also includes other components well known to those skilled in the art, such as communication buses and communication interfaces, the settings and functions of which are known in the art and will not be described in detail here.

Claims

1. A method for monitoring the attitude of transmission line towers based on multidimensional sensing, characterized in that, include: The original tilt angle time-series data of the transmission tower and the synchronous environmental state data were collected. The data were preprocessed using a sliding window mechanism to construct a time-varying environmental turbulence energy index, which is used to quantify the disturbance intensity of environmental load on the tower from a dynamic perspective. Based on the aforementioned environmental turbulence energy index, a nonlinear adaptive observation impedance is constructed using the hyperbolic tangent function; A quasi-static equilibrium evolution model incorporating the adaptive observation impedance is constructed, and the true settlement vector of the tower is iteratively updated by combining the directional consistency factor. The quasi-static equilibrium evolution model uses the reciprocal of the adaptive observation impedance as the dynamic update step size, and uses the directional consistency factor, which reflects the cosine of the angle between the current measurement increment direction and the historical settlement trend direction, to weight the update amplitude in order to shield against reciprocating oscillation interference. The comprehensive tilt is calculated based on the true value settlement vector, and a corresponding multi-level early warning mechanism is triggered according to the preset geological hazard classification standard for goaf areas.

2. The method for monitoring the attitude of transmission line towers based on multi-dimensional sensing according to claim 1, characterized in that, The formula for calculating the environmental turbulence energy index is: ； In the formula, Indicates time Environmental turbulence energy index; Indicates the length of the sliding time window; This represents any point in the sliding time window; Indicates time The original tilt angle vector; This represents the derivative of the original tilt angle vector with respect to time. Represents the Euclidean norm operation for vectors; Indicates time Ambient temperature; Indicates time Ambient temperature; Indicates the reference temperature constant; This represents the natural exponential function.

3. The method for monitoring the attitude of transmission line towers based on multi-dimensional sensing according to claim 1, characterized in that, The formula for calculating the adaptive observation impedance is: ； In the formula, Indicates time Adaptive observation impedance; The reference impedance is obtained through actual measurement and calculation, and corresponds to the basic sensitivity of the system under calm weather conditions. Indicates the impedance gain coefficient; Represents the hyperbolic tangent function; Indicates time Environmental turbulence energy index; This represents the potential energy threshold.

4. The method for monitoring the attitude of transmission line towers based on multi-dimensional sensing according to claim 1, characterized in that, The formula for calculating the true settlement vector is: ； In the formula, Indicates time The estimated ground truth sedimentation vector after denoising; Indicates time The estimated true settlement vector; Indicates time The original tilt angle vector; Indicates time Adaptive observation impedance; It represents the dimension conversion factor, the value of which is equal to the unit impedance value; This indicates that the step size is updated dynamically. Indicates time The directional consistency factor.

5. The method for monitoring the attitude of transmission line towers based on multi-dimensional sensing according to claim 1, characterized in that, The method for obtaining the directional consistency factor is as follows: The cosine of the angle between the current measurement increment vector and the historical settlement trend vector calculated based on a long time window is used as the directional consistency factor by performing a dot product operation.

6. The method for monitoring the attitude of transmission line towers based on multi-dimensional sensing according to claim 1, characterized in that, The time-series data of the original tilt angle of the transmission tower and the synchronized environmental status data include: A dual-axis tilt sensor installed on the crossarm of the transmission tower collects the original tilt angle vector containing tilt angle components along the line and tilt angle components across the line at a set sampling rate in real time; and a temperature probe integrated inside the dual-axis tilt sensor obtains the synchronous ambient temperature of the tower surface.

7. The method for monitoring the attitude of transmission line towers based on multi-dimensional sensing according to claim 1, characterized in that, The calculation of the overall tilt angle based on the true settlement vector includes: calculating the modulus of the true settlement vector; calculating the tangent value of the modulus using the tangent function, and multiplying the tangent value by a conversion factor from meters to millimeters to obtain the overall tilt angle of the tower in millimeters per meter.

8. The method for monitoring the attitude of transmission line towers based on multi-dimensional sensing according to claim 1, characterized in that, The triggering of the corresponding multi-level early warning mechanism includes: If the overall tilt exceeds the first-level threshold, a blue alert is triggered, and the sampling frequency is automatically encrypted; if the overall tilt exceeds the second-level threshold, a yellow alert is triggered, and a trend prediction report is sent; if the overall tilt exceeds the third-level threshold, a red alert is triggered, and the video surveillance system is activated to capture images of the scene.

9. The method for monitoring the attitude of transmission line towers based on multi-dimensional sensing according to claim 8, characterized in that, The first-level threshold is less than the second-level threshold, and the second-level threshold is less than the third-level threshold.

10. A transmission line tower attitude monitoring system based on multi-dimensional sensing, characterized in that, include: A processor and a memory, wherein the memory stores computer program instructions that, when executed by the processor, implement a method for monitoring the attitude of transmission line towers based on multidimensional sensing according to any one of claims 1-9.

Images