A Method and System for Monitoring the Attitude of Electric Pole Guy Wires Based on Multi-Sensor Data Fusion

Abstract

This invention belongs to the field of power facility monitoring technology, specifically relating to a method and system for monitoring the attitude of utility pole guy wires based on multi-sensor data fusion, aiming to solve the problems of delayed early warning and insufficient basis for maintenance decisions. The invention includes: acquiring angle and displacement data collected by multiple sensors on the utility pole guy wire; standardizing the data to construct a comprehensive dataset containing angular and displacement features; utilizing the synergistic relationship between the orientation measurement characteristics of the angle data and the deformation measurement characteristics of the displacement data, generating feature data describing the comprehensive spatial state of the guy wire through a weighted fusion algorithm; inputting the feature data into a mechanical analytical model established based on force equilibrium conditions and geometric constraints, and obtaining the real-time spatial attitude parameters of the utility pole guy wire by solving the model. This invention achieves accurate monitoring of the spatial attitude of utility pole guy wires, providing reliable technical support for the safe operation of power facilities.

Description

Technical Field

[0001] This invention belongs to the field of power facility monitoring technology, and specifically relates to a method and system for monitoring the attitude of utility pole guy wires based on multi-sensor data fusion. Background Technology

[0002] Pole guy wires are crucial support structures in power transmission lines, and their spatial stability directly affects the safe operation of the power lines. In practical applications, due to long-term exposure to external environmental loads such as wind and ice loads, as well as the effects of material creep, the spatial orientation of pole guy wires may change, leading to abnormal tension distribution. In severe cases, this can cause guy wires to loosen or even break, resulting in safety accidents such as pole overturning.

[0003] Currently, monitoring the condition of utility pole guy wires mainly relies on manual inspections or single-sensor monitoring. Manual inspections suffer from low efficiency, long cycles, and poor real-time performance, making it difficult to detect gradual deformation of the guy wires in a timely manner. Single-sensor monitoring, such as using only angle or displacement sensors, fails to comprehensively reflect the spatial attitude of the guy wires due to its limited monitoring dimension. While angle sensors can measure the tilt angle of the guy wires, they cannot accurately reflect the specific deformation; displacement sensors can measure local deformation but cannot comprehensively characterize the overall spatial orientation of the guy wires. This single-dimensional monitoring method suffers from incomplete monitoring information and limited measurement accuracy, making it difficult to accurately calculate the actual spatial attitude parameters of the guy wires and failing to provide reliable data support for assessing the safety status of the guy wires.

[0004] Furthermore, existing monitoring methods mostly remain at the data acquisition level, lacking effective fusion and processing of multi-source monitoring data, and failing to establish accurate analytical models based on the mechanical properties of the guy wire. This results in the inability to accurately calculate the spatial attitude and assess the state of the guy wire. Therefore, there is an urgent need for a method that can integrate multi-sensor data and combine it with the mechanical properties of the guy wire for accurate attitude monitoring. This would solve the technical problems of existing technologies, such as single monitoring dimensions, insufficient data utilization, inaccurate attitude calculation leading to distortion of the true spatial shape of the guy wire, difficulty in effectively capturing abnormal tension distribution, and consequently, delayed early warnings and insufficient basis for maintenance decisions. Summary of the Invention

[0005] To address the aforementioned problems in existing technologies, namely the distortion of the actual spatial shape of the guy wire and the difficulty in effectively capturing abnormal tension distribution, which leads to delayed early warnings and insufficient basis for maintenance decisions, this invention provides a method and system for monitoring the attitude of guy wires on utility poles based on multi-sensor data fusion.

[0006] In a first aspect, the present invention proposes a method for monitoring the attitude of guy wires on utility poles based on multi-sensor data fusion, the method comprising:

[0007] Acquire raw monitoring data collected by multiple sensors installed on the guy wire of the utility pole, the raw monitoring data including angle data and displacement data of the guy wire;

[0008] The original monitoring data is standardized to generate standardized data with a unified spatiotemporal reference.

[0009] The standardized data are combined according to preset physical quantity association rules to construct a comprehensive data set containing angular and displacement features.

[0010] The comprehensive dataset is subjected to multi-source data fusion calculation. The synergistic relationship between the orientation measurement characteristics of angle data and the deformation measurement characteristics of displacement data is utilized to generate feature data describing the comprehensive spatial state of the guy wire through a weighted fusion algorithm. The feature data includes the position and shape information of the guy wire in three-dimensional space.

[0011] The feature data is input into the pole guy wire mechanical analytical model. The real-time spatial attitude parameters of the pole guy wire are obtained by solving the mechanical analytical model. The pole guy wire mechanical analytical model is established based on the force balance condition and geometric constraint relationship of the guy wire. The mechanical analytical model solves the spatial attitude of the guy wire by establishing the correspondence between tension distribution and spatial coordinates.

[0012] Furthermore, the multi-source data fusion calculation is performed on the comprehensive dataset, and the method is as follows:

[0013] Angular features and displacement features are extracted from the comprehensive dataset, respectively.

[0014] Obtain the measurement error range of the angle sensor and the displacement sensor under standard testing conditions;

[0015] A first weighting coefficient is assigned to the angle feature based on the measurement error range, and a second weighting coefficient is assigned to the displacement feature based on the measurement error range, wherein the measurement error range is inversely proportional to the weighting coefficient assigned to the sensor data;

[0016] Using the first weighting coefficient and the second weighting coefficient, the angular feature quantity and the displacement feature quantity are weighted and fused to obtain the position information of the string in three-dimensional space;

[0017] Based on the location information and deformation measurement data in the displacement characteristics, feature data describing the overall spatial state of the guy wire is generated.

[0018] Furthermore, the method for generating feature data describing the overall spatial state of the guy wire based on deformation measurement data from location information and displacement characteristics is as follows:

[0019] The reference shape of the wire in three-dimensional space is determined based on the location information;

[0020] By combining the deformation measurement data in the displacement characteristic quantities, the spatial deformation of the wire relative to the reference shape is calculated;

[0021] Based on the aforementioned spatial deformation and baseline shape, determine the actual spatial shape parameters of the wire;

[0022] The location information and spatial morphological parameters are combined according to a preset data structure, wherein the location information serves as a spatial reference and the spatial morphological parameters serve as morphological feature descriptions, together constituting the feature data.

[0023] Furthermore, the method for establishing the analytical mechanical model of the pole guy wire includes:

[0024] Establish a spatial rectangular coordinate system for the guy wires and determine the spatial coordinates of the fixed points at both ends of the guy wires;

[0025] Obtain the material properties and structural parameters of the guy wire;

[0026] Based on the aforementioned structural parameters, a set of force balance equations for the internal tension of the guy wire and the external load is established.

[0027] Based on the coordinates of the fixed points at both ends of the guy wire and the actual length of the guy wire, a set of geometric constraint equations for the spatial position and length variation of the guy wire is established.

[0028] By combining the force equilibrium equations and the geometric constraint equations, a mathematical relationship between the spatial position of the tension wire and the tension distribution can be constructed.

[0029] The mathematical relationship is transformed into a computational model that can calculate attitude parameters by inputting feature data through numerical calculation methods.

[0030] Furthermore, the material property parameters include elastic modulus and material density; the structural parameters include original length and cross-sectional area; and the external loads include self-weight load and environmental load.

[0031] The numerical calculation method includes establishing a discretized calculation model and configuring an iterative calculation algorithm.

[0032] Furthermore, the mechanical analytical model calculates the spatial attitude of the tension cable by establishing the correspondence between tension distribution and spatial coordinates. The method is as follows:

[0033] Based on the input feature data, set the initial iteration value for the spatial position of the drawstring;

[0034] Based on the force equilibrium condition, calculate the internal tension distribution of the guy wire corresponding to the current spatial position;

[0035] Based on the aforementioned geometric constraints, verify the degree of matching between the actual length of the pull-down cable under the current tension distribution and the spatial coordinates;

[0036] Based on the verification results, the iterative value of the spatial position is adjusted, the tension distribution inside the guy wire corresponding to the adjusted spatial position is recalculated, and the matching degree between the actual length of the guy wire and the spatial coordinates is verified again.

[0037] Repeat the recalculation and verification steps until the preset convergence condition is met;

[0038] The spatial coordinates determined by the final iteration are converted into the real-time spatial attitude parameters of the guy wire.

[0039] Furthermore, the standardized data is combined according to preset physical quantity association rules to construct a comprehensive dataset containing angular and displacement features. The method is as follows:

[0040] The standardized data are classified according to their physical quantity type, and angle feature identifiers are assigned to angle data and displacement feature identifiers are assigned to displacement data.

[0041] Based on the timestamp information and spatial coordinate information carried in the standardized data, angular and displacement features with the same time and spatial references are associated.

[0042] Perform a data integrity check on the associated angle and displacement features to ensure that the angle and displacement features at each time point are completely corresponding.

[0043] The angular and displacement features that have passed the integrity check are organized according to the time series to form the comprehensive data set.

[0044] Furthermore, the method also includes the following steps:

[0045] Compare real-time spatial attitude parameters with a preset safety threshold range;

[0046] When the real-time spatial attitude parameters exceed the safety threshold range, a preset pull-wire status warning message is generated;

[0047] Based on the type and level of the cable status warning information, corresponding maintenance decision suggestions are output.

[0048] Furthermore, the plurality of sensors include angle sensors and displacement sensors, which are distributed at preset intervals along the length of the guy wire.

[0049] In a second aspect, the present invention proposes a method and system for monitoring the attitude of guy wires on utility poles based on multi-sensor data fusion, for executing a method for monitoring the attitude of guy wires on utility poles based on multi-sensor data fusion, the system comprising:

[0050] The data acquisition module is configured to acquire raw monitoring data collected by multiple sensors installed on the guy wire of the utility pole, the raw monitoring data including angle data and displacement data of the guy wire;

[0051] The standardization processing module is configured to perform standardization processing on the original monitoring data to generate standardized data with a unified spatiotemporal reference.

[0052] The dataset construction module is configured to combine the standardized data according to preset physical quantity association rules to construct a comprehensive dataset containing angular and displacement features.

[0053] The multi-source fusion computing module is configured to perform multi-source data fusion computing on the comprehensive dataset. It utilizes the synergistic relationship between the orientation measurement characteristics of angle data and the deformation measurement characteristics of displacement data to generate feature data describing the comprehensive spatial state of the guy wire through a weighted fusion algorithm. The feature data includes the position and shape information of the guy wire in three-dimensional space.

[0054] The spatial attitude calculation module is configured to input the feature data into the pole guy wire mechanical analytical model, and obtain the real-time spatial attitude parameters of the pole guy wire by solving the mechanical analytical model. The pole guy wire mechanical analytical model is established based on the force balance condition and geometric constraint relationship of the guy wire. The mechanical analytical model solves the spatial attitude of the guy wire by establishing the correspondence between tension distribution and spatial coordinates.

[0055] The beneficial effects of this invention are:

[0056] This invention overcomes the shortcomings of existing technologies that use a single sensor for monitoring, such as limited monitoring dimensions and incomplete information, by simultaneously deploying angle and displacement sensors and constructing a comprehensive dataset containing both angular and displacement characteristics. This method can simultaneously acquire the orientation and deformation information of the guy wire, providing a complete data foundation for a comprehensive and accurate assessment of the guy wire's spatial state.

[0057] This invention standardizes the original monitoring data, unifies the spatiotemporal reference, and utilizes the synergistic relationship between the orientation measurement characteristics of angle data and the deformation measurement characteristics of displacement data through multi-source data fusion calculation. By employing a weighted fusion algorithm based on the measurement error range, it effectively reduces the impact of measurement errors from a single sensor and significantly improves the accuracy and reliability of feature data.

[0058] This invention establishes a mechanical analytical model of utility pole guy wires based on the force equilibrium conditions and geometric constraints, closely integrating sensor monitoring data with the mechanical properties of the guy wires. This overcomes the limitations of traditional methods that rely solely on simple threshold judgments. This analytical method based on physical mechanisms can accurately reflect the actual force state of the guy wires, achieving precise conversion from monitoring data to spatial attitude parameters.

[0059] This invention compares real-time spatial attitude parameters with preset safety thresholds, enabling timely detection of abnormal cable conditions and generating targeted early warning information and maintenance decision suggestions. This transforms the process from passive inspection to proactive early warning, effectively preventing safety accidents caused by deteriorating cable conditions.

[0060] This invention automates the entire process from data acquisition, processing, and fusion to attitude calculation and state diagnosis, significantly reducing the need for manual intervention and overcoming the shortcomings of low efficiency and long cycle of manual inspection. It provides reliable technical support for realizing real-time and continuous monitoring of pole guy wires. Attached Figure Description

[0061] Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0062] Figure 1 This is a schematic diagram of the overall process of the pole guy wire attitude monitoring method based on multi-sensor data fusion of the present invention;

[0063] Figure 2 This is a schematic diagram of the multi-source data fusion calculation process of the pole guy wire attitude monitoring method based on multi-sensor data fusion of the present invention;

[0064] Figure 3 This is a flowchart of the mechanical analytical model solution process for the pole guy wire attitude monitoring method based on multi-sensor data fusion of the present invention;

[0065] Figure 4 This is a flowchart of the early warning processing flow of the pole guy wire attitude monitoring method based on multi-sensor data fusion of the present invention;

[0066] Figure 5 This is a schematic diagram of the structure of a computer system used to implement the methods, systems, and electronic devices of this application. Detailed Implementation

[0067] The present application will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the invention. Furthermore, it should be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings.

[0068] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0069] The first embodiment of the present invention provides a method for monitoring the attitude of utility pole guy wires based on multi-sensor data fusion, the method comprising:

[0070] Step S10: Obtain raw monitoring data collected by multiple sensors installed on the guy wire of the utility pole, the raw monitoring data including angle data and displacement data of the guy wire;

[0071] Step S20: Standardize the original monitoring data to generate standardized data with a unified spatiotemporal reference.

[0072] Step S30: Combine the standardized data according to the preset physical quantity association rules to construct a comprehensive data set containing angular feature quantities and displacement feature quantities;

[0073] Step S40: Perform multi-source data fusion calculation on the comprehensive data set, wherein the synergistic relationship between the orientation measurement characteristics of angle data and the deformation measurement characteristics of displacement data is utilized to generate feature data describing the comprehensive spatial state of the guy wire through a weighted fusion algorithm. The feature data includes the position and shape information of the guy wire in three-dimensional space.

[0074] Step S50: Input the feature data into the pole guy wire mechanical analytical model, and obtain the real-time spatial attitude parameters of the pole guy wire by solving the mechanical analytical model. The pole guy wire mechanical analytical model is established based on the force balance condition and geometric constraint relationship of the guy wire. The mechanical analytical model calculates the spatial attitude of the guy wire by establishing the correspondence between tension distribution and spatial coordinates.

[0075] To more clearly illustrate the pole guy wire attitude monitoring method based on multi-sensor data fusion of the present invention, the following will be combined with... Figure 1 The steps in the embodiments of the present invention are described in detail below, including steps S10-S50:

[0076] Step S10: Obtain raw monitoring data collected by multiple sensors installed on the guy wire of the utility pole, the raw monitoring data including angle data and displacement data of the guy wire;

[0077] In this embodiment, the plurality of sensors include angle sensors and displacement sensors, which are distributed at preset intervals along the length of the guy wire.

[0078] In practical implementation, the first step is to select and configure the sensors. A triaxial MEMS tilt sensor is selected for the angle, with a range of ±30°, an accuracy of 0.1°, and an operating temperature range of -40℃ to +85℃. A draw-wire displacement sensor is selected for the displacement, with a range of 500mm, an accuracy of 0.5mm, and an IP67 protection rating. The sensor arrangement is determined based on the actual length of the draw-wire. For a standard 30-meter draw-wire, the preset spacing is 2-3 meters. Measurement nodes are arranged at the upper, middle, and lower ends of the draw-wire, with both an angle sensor and a displacement sensor installed at each node. During installation, the angle sensor is fixed to the surface of the draw-wire using a special clamp, ensuring that the sensor axis is parallel to the draw-wire axis. One end of the displacement sensor is fixed to the support point at the upper end of the draw-wire, and the other end is connected to the measurement point in the middle of the draw-wire to measure the relative displacement change of the draw-wire.

[0079] During actual installation, the pull wire is first segmented and marked to determine the installation position of each sensor. Rust-proof bolts are used to fix the sensor mounting base to the pull wire, ensuring that the base plane is perpendicular to the tangent direction of the pull wire. Angle sensors are connected to the base via aviation connectors, and displacement sensors are connected to the measurement point via stainless steel pull ropes; all connections are designed to prevent loosening. The sensors are powered by a solar power system, and data transmission uses an RS485 bus. Each sensor is connected in parallel to the data acquisition unit via shielded twisted-pair cables.

[0080] In terms of data acquisition system configuration, the sampling frequency is set to 10Hz, and the collector has a built-in storage module that can cache 72 hours of monitoring data. After the system is powered on, it first performs a sensor self-test to confirm that each sensor is working properly before starting data acquisition. The acquired raw data includes a timestamp, sensor ID, measurement value, and status code, and is transmitted to the monitoring center via a wireless transmission module. To ensure data reliability, the system adopts a cyclic acquisition mechanism; when a sensor fails, it automatically switches to a backup acquisition channel.

[0081] The advantage of this multi-sensor distributed deployment method is that it can comprehensively capture the attitude changes of the guy wire in different sections. Multi-point measurement effectively avoids the limitations of single-point measurement, providing a rich foundation of raw data for subsequent data fusion and analysis. At the same time, the reasonable spacing ensures both comprehensive monitoring and avoids mutual interference between sensors, guaranteeing the accuracy and reliability of the monitoring data.

[0082] Step S20: Standardize the original monitoring data to generate standardized data with a unified spatiotemporal reference.

[0083] In practical implementation, the standardization process includes two key aspects: time synchronization and spatial coordinate unification. In time synchronization, the system first reads the local timestamps from the data packets of each sensor. These timestamps originate from the GPS / BeiDou dual-mode positioning module installed at each sensor node. The time synchronization processor uses the master clock of the monitoring center as a reference and employs the NTP network time protocol to calibrate the time of each sensor node, uniformly converting the collected time to the UTC standard time format. For time deviations caused by network latency, the system uses a linear interpolation method to resample the data, ensuring that all sensor data achieves millisecond-level time synchronization accuracy. In practice, the time synchronization period is set to 1 hour. When a time deviation of more than 50 milliseconds is detected at a sensor node, a forced synchronization procedure is immediately initiated.

[0084] In the unified spatial coordinate processing, a global rectangular coordinate system is first established with the center of the pole's base as the origin, north as the positive X-axis, east as the positive Y-axis, and the vertical upward direction as the positive Z-axis. Local coordinate system data collected by each sensor is transformed to this global coordinate system using a coordinate transformation matrix. For angle sensor data, the measured tilt angle readings are converted to spatial azimuth angles in the global coordinate system; for displacement sensor data, the measured relative displacement values ​​are converted to absolute coordinate values ​​in the global coordinate system. During the coordinate transformation process, sensor installation position and orientation deviations must be considered and compensated for using pre-calibrated installation parameters. In practice, a total station is used to accurately measure the actual installation positions of each sensor, obtain installation offset parameters, and establish a transformation matrix between the sensor's local coordinate system and the global coordinate system.

[0085] After the above standardization process, each data point contains a unified timestamp and global spatial coordinates, forming a standardized data sequence with a consistent spatiotemporal reference. This standardization process ensures a unified reference benchmark for subsequent multi-sensor data fusion, effectively eliminating systematic errors caused by sensor heterogeneity and providing a reliable data foundation for accurately analyzing the spatial attitude changes of the guy wire. The processed standardized data is stored according to a data structure of timestamp, spatial coordinates, and physical quantity values, facilitating subsequent data retrieval and analysis.

[0086] Step S30: Combine the standardized data according to the preset physical quantity association rules to construct a comprehensive data set containing angular feature quantities and displacement feature quantities;

[0087] Specifically, step S30 includes:

[0088] Step S31: Classify the standardized data according to their physical quantity type, assign angle feature quantity identifiers to angle data, and assign displacement feature quantity identifiers to displacement data.

[0089] Step S32: Based on the timestamp information and spatial coordinate information carried in the standardized data, associate the angular feature quantities and displacement feature quantities with the same time reference and spatial reference.

[0090] Step S33: Perform a data integrity check on the associated angle feature quantity and displacement feature quantity to ensure that the angle feature quantity and displacement feature quantity at each time point are completely corresponding.

[0091] Step S34: Organize the angle feature quantities and displacement feature quantities that have passed the integrity check according to the time series to construct the comprehensive data set.

[0092] In specific implementation, in step S31, the system first establishes a physical quantity classification rule base, defining the feature identifier for angle data as "ANG_" prefixed with the sensor number, and the feature identifier for displacement data as "DISP_" prefixed with the sensor number. The system traverses all standardized data, automatically marking the data of the triaxial tilt sensor as an angle feature quantity and the data of the draw-wire displacement sensor as a displacement feature quantity by parsing the sensor type field in the data packet. For example, the data of angle sensor No. 1 is identified as "ANG_001", and the data of displacement sensor No. 3 is identified as "DISP_003". The metadata information corresponding to each identifier, including parameters such as sensor model, range, and accuracy level, is synchronously recorded in the feature quantity description file.

[0093] In step S32, the system performs initial association of angle and displacement features with the same GPS timestamp within a 10-millisecond time window. For spatial reference association, the system calculates the spatial distance between each sensor measurement point in the global coordinate system. When the spatial distance between the measurement points of two features is less than a preset threshold of 0.1 meters, they are determined to have the same spatial reference. In specific implementation, the system establishes a spatiotemporal association matrix, where rows represent time series and columns represent spatial locations. A spatiotemporal hashing algorithm is used to quickly match features with the same spatiotemporal reference. For data that cannot be precisely matched, the system uses bilinear interpolation to align the data, ensuring that each spatial location has corresponding angle and displacement features at each time point.

[0094] The data integrity check in step S33 includes three levels: First, it checks whether each time point simultaneously contains both angle and displacement features, marking any missing data. Second, it checks the reasonableness of the data values; angle data is limited to a range of -30° to +30°, and displacement data is limited to a range of -500mm to +500mm; data outside these ranges are considered abnormal. Finally, it checks the continuity of the data by calculating the rate of change of data between adjacent time points and eliminating abrupt abnormal data. The system sets an integrity threshold of 95%. When the data integrity at a certain time point falls below this threshold, a data reconstruction mechanism is automatically triggered, using valid data from preceding and following time points to complete the missing data through cubic spline interpolation.

[0095] In step S34, the system organizes the examined feature quantities into a comprehensive dataset according to time series. This dataset adopts a hierarchical storage structure: the top layer is the time index layer, indexed by second-level timestamps; the middle layer is the spatial location layer, recording the spatial coordinates of each measurement point; and the bottom layer is the feature data layer, storing specific angle and displacement measurements. The dataset is stored in HDF5 format, supporting fast time range queries and spatial location retrieval. The system also generates a metadata file for the dataset, recording statistical information such as the total data volume, time span, and spatial distribution. The advantage of this organization is that it maintains the spatiotemporal correlation of the data while facilitating subsequent data access and processing, providing a complete and standardized data foundation for multi-sensor data fusion.

[0096] To more clearly explain the solution of this invention, please refer to the following example:

[0097] The system processes standardized data from five sensors: three angle sensors (numbered 001-003) and two displacement sensors (numbered 004-005). The system assigns characteristic identifiers to these data: angle sensor data (number 001) is labeled "ANG_001," with metadata recording sensor model JY-61, a range of ±30°, and an accuracy of 0.1°; displacement sensor data (number 004) is labeled "DISP_004," with metadata recording sensor model WDS-500, a range of 500mm, and an accuracy of 0.5mm. The other sensors follow the same pattern, establishing a complete characteristic identifier system.

[0098] The system processes data from 10:00:00:000 milliseconds on June 15, 2024. First, time window matching reveals that "ANG_001" and "DISP_004" have the same timestamp. Then, spatial coordinates are calculated: the installation location coordinates of "ANG_001" are (1.2, 3.4, 5.6), and the installation location coordinates of "DISP_004" are (1.25, 3.38, 5.58). The spatial distance between them is... If the value is less than the 0.1m threshold, it is determined that the data has the same spatial reference and an association is established. For data with a timestamp of 10:00:00:050 milliseconds, if "ANG_002" lacks corresponding displacement data, the system will interpolate the displacement data from the time points before and after it (10:00:00:00 milliseconds and 10:00:00:100 milliseconds) to obtain the estimated value at that time.

[0099] Checking the associated data at 10:00:00:00 milliseconds, it was found that all five measurement points simultaneously contained both angle and displacement characteristics, indicating complete data. In the numerical reasonableness check, the angle value of "ANG_001" was 15.3°, within the normal range; the displacement value of "DISP_004" was 125.6 mm, within the measurement range. In the continuity check, the rate of change of "ANG_001" at adjacent time points (10:00:00:00 milliseconds and 10:00:00:100 milliseconds) was calculated to be 0.5° / s, less than the set threshold of 2° / s, and was therefore considered normal. If, at a certain moment, the value of "ANG_003" is 35°, exceeding the measurement range, the system will mark this data as abnormal and calculate a replacement value of 28.7° using the preceding and following normal data through cubic spline interpolation.

[0100] All checked features from 10:00:00 to 10:00:01 on June 15, 2024, were organized into a time series. At the time index layer, an index sequence in milliseconds was created; at the spatial location layer, the spatial coordinates of five measurement points were recorded; and at the feature data layer, the angle and displacement measurements at each time point were stored. The final dataset contains 100 time points (10Hz sampling frequency), five spatial locations, and a total of 1000 feature data points (100×5×2). This dataset is stored in HDF5 format, with a file size of approximately 85KB, and a metadata file is generated to record the total amount of data, time span, and spatial distribution information. This complete example demonstrates the entire processing flow from raw data to a normalized dataset, ensuring data integrity and usability.

[0101] See Figure 2 Step S40: Perform multi-source data fusion calculation on the comprehensive data set, wherein the synergistic relationship between the orientation measurement characteristics of angle data and the deformation measurement characteristics of displacement data is utilized to generate feature data describing the comprehensive spatial state of the guy wire through a weighted fusion algorithm. The feature data includes the position and shape information of the guy wire in three-dimensional space.

[0102] In this embodiment, the method for performing multi-source data fusion calculation on the comprehensive dataset is as follows:

[0103] Step S41: Extract angular and displacement features from the integrated dataset, respectively.

[0104] Step S42: Obtain the measurement error range of the angle sensor and the displacement sensor under the standard test environment.

[0105] Step S43: Assign a first weighting coefficient to the angle feature based on the measurement error range, and assign a second weighting coefficient to the displacement feature based on the measurement error range, wherein the measurement error range is inversely proportional to the weighting coefficient assigned to the sensor data;

[0106] Step S44: Using the first weighting coefficient and the second weighting coefficient, perform weighted fusion calculation on the angle feature quantity and the displacement feature quantity to obtain the position information of the pull line in three-dimensional space;

[0107] Step S45: Based on the position information and deformation measurement data in the displacement feature quantities, generate feature data describing the overall spatial state of the guy wire.

[0108] Step S45 involves generating feature data describing the overall spatial state of the guy wire based on the location information and deformation measurement data in the displacement feature quantities, including:

[0109] Step S451: Determine the reference shape of the pull wire in three-dimensional space based on the position information;

[0110] Step S452: Combine the deformation measurement data in the displacement characteristic quantities to calculate the spatial deformation of the wire relative to the reference shape;

[0111] Step S453: Based on the spatial deformation and reference shape, determine the actual spatial shape parameters of the wire;

[0112] Step S454: The location information and spatial morphological parameters are combined according to a preset data structure, wherein the location information serves as a spatial reference and the spatial morphological parameters serve as a morphological feature description, together constituting the feature data.

[0113] In step S41, when extracting angular and displacement features from the comprehensive dataset, engineers first open the HDF5 data file and use professional data processing software to read the feature data layer. For example, when processing data from 10:00:00 on June 15, 2024, five angular feature readings were extracted from the dataset: ANG_001: 15.3°, ANG_002: 16.1°, and ANG_003: 14.8°, along with five corresponding displacement feature readings: DISP_004: 125.6 mm and DISP_005: 118.3 mm. During the extraction process, the quality identifier and data acquisition timestamp of each feature were recorded simultaneously to ensure data traceability.

[0114] In step S42, when obtaining the sensor measurement error range, engineers consult the sensor calibration report. For example, according to calibration certificate number CAL-2024-001, the measurement error range of angle sensor JY-61 under standard laboratory conditions (temperature 20℃±1℃, humidity 50%±5%) is ±0.1°, and the measurement error range of displacement sensor WDS-500 under the same conditions is ±0.5mm. These error range data are recorded in the quality control file as the basis for subsequent weight calculations.

[0115] In step S43, when allocating weighting coefficients, a weighting allocation method based on measurement accuracy is adopted. The specific calculation process is as follows: First, the uncertainty components of each sensor are calculated, including the uncertainty of the angle sensor. Uncertainty of displacement sensor Then calculate the weighting coefficients, specifically the angle sensor weight w. a =1 / (0.0577) 2 =300, displacement sensor weight w d =1 / (0.2887) 2 =12. After normalization, the first weighting coefficient of the angle feature is 300 / (300+12)=0.9615, and the second weighting coefficient of the displacement feature is 12 / (300+12)=0.0385. These weighting coefficients are recorded in the fusion parameter configuration table.

[0116] Step S44, the weighted fusion calculation, is illustrated using measurement point P1 as an example. At this point, the angle sensor reading is 15.3°, and the displacement sensor reading is 125.6 mm. First, the displacement value is converted to an angle representation, and the equivalent angle of 15.8° is calculated using geometric relationships. Then, weighted fusion is performed: Fusion value = 15.3° × 0.9615 + 15.8° × 0.0385 = 15.32°. Simultaneously, the elevation angle is calculated in the same way, ultimately yielding the fused spatial coordinates of the measurement point (1.253, 3.382, 5.583). All measurement points are calculated in parallel using this method, and the intermediate results of each step are recorded in the data log table.

[0117] The specific implementation of step S45, generating feature data, includes: In step S451, using cubic spline interpolation to fit the baseline shape of the guy wire based on the fused position data. For example, using the spatial coordinates of 5 measurement points, the spatial curve equation of the guy wire is generated, with a total curve length of 28.6 meters and a maximum curvature of 0.18 meters. -1 In step S452, the spatial deformation of each measurement point relative to the reference shape is calculated. For example, the actual distance between the measurement point P3 and the reference curve is 15.2 mm; this value is the spatial deformation. In step S453, the actual spatial shape parameters are calculated based on the deformation, including the rate of change of curvature of 0.02 m. -2 Parameters such as deformation gradient 0.008 are included. In step S454, the position information and morphological parameters are combined according to a hierarchical data structure. The generated feature data contains complete information such as spatial coordinates, deformation, and curvature, and is stored in a feature data file for subsequent use.

[0118] In summary, assuming the system processes data from measurement point P1 (sensors ANG_001 and DISP_004) at 10:00:00 on June 15, 2024, the generated feature data after the complete process includes: fused spatial coordinates (1.253, 3.382, 5.583), deformation of 12.5 mm, and curvature of 0.15 m. -1 Deflection 0.08m -1 These parameters are organized according to a preset data structure to form a complete state description unit. The state description units of all measurement points are organized according to a time series, ultimately forming a feature dataset of the overall spatial state of the wire harness.

[0119] This embodiment leverages the synergistic relationship between the orientation measurement characteristics of angle data and the deformation measurement characteristics of displacement data to achieve complementary advantages of different sensor data, effectively overcoming the limitations of single-sensor monitoring. Angle sensors offer high accuracy in measuring orientation but are insufficient in reflecting specific deformations; displacement sensors accurately measure deformation but have relatively low accuracy in determining spatial orientation. By employing a weighted fusion algorithm, the advantages of both are organically combined, significantly improving the accuracy and reliability of spatial location information.

[0120] A weighting method based on sensor measurement error ranges ensures the scientific rigor and rationality of data fusion. By using accurate error range data obtained under standard laboratory conditions, appropriate weighting coefficients are assigned to different sensor data, allowing the more accurate sensor data to play a greater role in the fusion process. This weighting strategy effectively suppresses the propagation and amplification of measurement errors, improving the accuracy of the fused feature data.

[0121] By establishing a complete feature data generation process, a comprehensive description of the spatial state of the guy wires was achieved. By organically combining location information with morphological parameters, both the overall spatial orientation of the guy wires and its local deformation characteristics were reflected. This multi-dimensional feature description method provides richer and more accurate data support for accurately assessing the condition of guy wires. Engineering practice shows that the feature data generated by this method can more sensitively detect early deformation of guy wires, providing a reliable basis for preventative maintenance.

[0122] Step S50: Input the feature data into the pole guy wire mechanical analytical model, and obtain the real-time spatial attitude parameters of the pole guy wire by solving the mechanical analytical model. The pole guy wire mechanical analytical model is established based on the force balance condition and geometric constraint relationship of the guy wire. The mechanical analytical model calculates the spatial attitude of the guy wire by establishing the correspondence between tension distribution and spatial coordinates.

[0123] In this embodiment, the method for establishing the mechanical analytical model of the pole guy wire includes:

[0124] Step S51: Establish a spatial rectangular coordinate system for the guy wire and determine the spatial coordinates of the fixed points at both ends of the guy wire;

[0125] Step S52: Obtain the material property parameters and structural parameters of the draw wire; the material property parameters include the elastic modulus and material density, and the structural parameters include the original length and cross-sectional area;

[0126] Step S53: Establish a set of force balance equations for the internal tension of the guy wire and the external load based on the structural parameters; the external load includes the self-weight load and the environmental load.

[0127] Step S54: Based on the coordinates of the fixed points at both ends of the guy wire and the actual length of the guy wire, establish a set of geometric constraint equations for the spatial position and length variation of the guy wire;

[0128] Step S55: Combine the force equilibrium equations and the geometric constraint equations to construct the mathematical relationship between the spatial position of the tension wire and the tension distribution.

[0129] Step S56: The mathematical relationship is transformed into a computational model that can calculate attitude parameters by inputting feature data through numerical calculation methods. The numerical calculation methods include establishing a discretized calculation model and configuring an iterative calculation algorithm.

[0130] In the specific implementation of step S51, the center of the bottom of the pole is first selected as the origin of the coordinate system. North is defined as the positive X-axis, east as the positive Y-axis, and vertical upwards as the positive Z-axis, establishing a global spatial rectangular coordinate system. A total station is used to measure the precise spatial coordinates of the fixed points at both ends of the guy wire. For example, the upper fixed point might be located at the top of the pole, with coordinates (0,0,15) meters, while the lower fixed point is located at the ground anchor point, with coordinates (10,5,0) meters. During measurement, terrain undulations and installation deviations must be considered, and the coordinate accuracy is ensured by averaging multiple measurements. The advantage of this step is that it provides a unified geometric reference frame, ensuring spatial consistency in all subsequent calculations and avoiding error accumulation caused by inconsistent coordinate systems.

[0131] The specific implementation of step S52 involves collecting the material property parameters and structural parameters of the guy wire. The material property parameters are obtained from the product specifications provided by the guy wire manufacturer; for example, for common steel strand guy wire, the elastic modulus E is 200 GPa, and the material density ρ is 7850 kg / m³. 3 The structural parameters were obtained through design drawings or on-site measurements. The original length L0 is 30 meters, and the cross-sectional area A is 100 mm². 2 These parameters are recorded in a parameter database, along with the measurement date and source information, to ensure the reliability and traceability of the data. This step provides accurate physical property input to the mechanical model, ensuring the reliability of the model's fundamental data and laying the material foundation for precise calculations of the wire's behavior.

[0132] In the specific implementation of step S53, a set of force equilibrium equations is established based on the parameters of the guy wire structure. First, the self-weight load is calculated as a distributed load acting on the guy wire, with a linear density q = ρ × g × A, where g is the acceleration due to gravity (taken as 9.8 m / s²). 2 Environmental loads, such as wind loads, are calculated based on local meteorological data using the wind pressure formula F. wind =0.5×ρ air ×C d ×V wind2 ×D, where ρ air air density (1.2 kg / m³) 3 ), C d V is the drag coefficient (taken as 1.2). wind Where is the wind speed, and D is the guy wire diameter (e.g., 20mm). The force equilibrium equations include the force equilibrium equations for the infinitesimal segments of the guy wire, and the component equations in the X, Y, and Z directions. For example, in the X direction: d(T×dx / ds) / ds+F x =0, where T is the tension, s is the arc length parameter, and F x This represents the external load component in the X direction. The advantage of this step is that it quantifies the complex force situation into mathematical equations, which can accurately describe the mechanical behavior of the guy wire under various loads, providing a dynamic basis for attitude analysis.

[0133] In the specific implementation of step S54, a set of geometric constraint equations is established. First, the theoretical length is calculated based on the coordinates of the fixed points at both ends of the guy wire, taking into account the actual length change caused by elastic deformation. The relationship between the actual length L of the guy wire and the original length L0 is given by Hooke's Law: ΔL = L - L0 = (T avg ×L0) / (E×A), where T avg The average tension is determined. The geometric constraint equations include the curve equations representing the shape of the guy wire, such as using a catenary or parabolic model. The spatial coordinates (x, y, z) of the guy wire are associated with the arc length s. For example, for a catenary, z = a × cosh(x / a) + b, where a and b are parameters that must satisfy the endpoint coordinate constraints. The advantage of this step is that it couples the geometric shape with mechanical deformation, ensuring the model's spatial morphology is reasonable and accurately reflecting the actual shape changes of the guy wire.

[0134] In the specific implementation of step S55, the force equilibrium equations and geometric constraint equations are combined to construct a mathematical relationship. Through substitution and variable elimination, the two sets of equations are merged into a single system, for example, forming a system of nonlinear differential equations concerning tension T and coordinates (x, y, z). The mathematical relationship is expressed as: F(T, x, y, z) = 0, where F is a vector function containing force equilibrium and geometric constraints. The advantage of this step is that it integrates mechanical and geometric factors, forming a unified mathematical model, simplifying the subsequent solution process, and improving computational efficiency.

[0135] In the specific implementation of step S56, the mathematical relationship is transformed into a computational model through numerical calculation methods. First, a discretized computational model is established, dividing the guy wire into N small segments (e.g., N=100), each segment considered as a straight line element, and establishing force balance equations and geometric constraint equations at the nodes. Then, an iterative calculation algorithm, such as the Newton-Raphson method, is configured, setting initial guess values ​​(e.g., initial tension generated by its own weight), and iteratively solving the nonlinear equation system until the error norm is less than a preset tolerance (e.g., 1e-6). The computational model is implemented as a computer program, taking input feature data (e.g., position information after sensor fusion) and outputting attitude parameters (e.g., spatial coordinates and tension distribution). The advantage of this step is that it transforms complex mathematical problems into a computable form, enabling the model to process sensor data in real time, achieving dynamic monitoring and early warning of the guy wire's attitude.

[0136] After completing the above model establishment steps, a specific example will be used to illustrate the entire implementation process. Assume monitoring the guy wire of pole number 15 on a 110kV transmission line. This guy wire uses GJ-100 type steel strand. In step S51, the coordinates of the upper fixed point on the guy wire are measured using a total station as (0, 0, 18.5) m, and the coordinates of the lower fixed point are (12.3, 8.7, 0.2) m. In step S52, the elastic modulus E = 190 GPa and the material density ρ = 7850 kg / m³ are found from the material certificate. 3 The original length L0 = 22.6 m and the cross-sectional area A = 100 mm² 2 .

[0137] In step S53, the system of force equilibrium equations is established. First, the self-weight load is calculated: linear density q = ρ × g × A = 7850 × 9.8 × 100 × 10 -6 =7.693 N / m. Considering the local basic wind pressure of 0.35 kN / m. 2 The wind load distribution force is calculated to be 1.2 N / m. Equilibrium equations are established in three directions:

[0138] ;

[0139] In step S54, a system of geometric constraint equations is established. The relationship between the actual length L of the guy wire and its original length is as follows:

[0140] L=L0×(1+T avg / (E×A));

[0141] The space curve constraint equation is:

[0142] (dx / ds) 2 +(dy / ds) 2 +(dz / ds) 2 =1;

[0143] In step S55, the above equations are combined to obtain a set of nonlinear differential equations with respect to tension T and coordinates (x,y,z), which contains 6 independent equations.

[0144] In step S56, a numerical method is used to solve the problem. First, the guy wire is discretized into 50 elements, and the nodal force balance equations are established. The Newton-Raphson iterative method is used, with a convergence tolerance of 10. -6 The initial assumption was that the tension distribution was a parabolic distribution under its own weight, with a maximum tension of 1500 N. After 8 iterations, convergence was achieved, and the actual shape and tension distribution of the tension cable were calculated. For example, at the midpoint of the tension cable, the calculated coordinates were (6.15, 4.35, 9.8) m, and the tension was 1820 N, with an error of less than 3% compared to subsequent actual measurements.

[0145] This example demonstrates the complete model building and solution process, verifying the effectiveness and accuracy of the proposed method. This specific example shows that the established mechanical analytical model accurately reflects the actual stress state and spatial shape of the guy wire, providing a reliable theoretical basis for attitude monitoring. Practical applications show that the model maintains good computational accuracy even when considering various load conditions, meeting the requirements of engineering monitoring.

[0146] See Figure 3 In this embodiment, the mechanical analytical model calculates the spatial attitude of the tension cable by establishing the correspondence between tension distribution and spatial coordinates. The method is as follows:

[0147] Based on the input feature data, set the initial iteration value for the spatial position of the drawstring;

[0148] Based on the force equilibrium condition, calculate the internal tension distribution of the guy wire corresponding to the current spatial position;

[0149] Based on the aforementioned geometric constraints, verify the degree of matching between the actual length of the pull-down cable under the current tension distribution and the spatial coordinates;

[0150] Based on the verification results, the iterative value of the spatial position is adjusted, the tension distribution inside the guy wire corresponding to the adjusted spatial position is recalculated, and the matching degree between the actual length of the guy wire and the spatial coordinates is verified again.

[0151] Repeat the recalculation and verification steps until the preset convergence condition is met;

[0152] The spatial coordinates determined by the final iteration are converted into the real-time spatial attitude parameters of the guy wire.

[0153] In practice, the initial iteration values ​​for the spatial position of the guy wire are first set based on the input feature data. Taking the GJ-100 type guy wire of a certain tower as an example, the input feature data includes the spatial coordinates and morphological parameters of 5 monitoring points. The initial iteration values ​​are set using the parabolic approximation method. Assuming that the guy wire is in a parabolic shape under its own weight, the spatial position coordinates of each point under the initial shape are calculated based on the coordinates of the two fixed points at both ends (0,0,18.5)m and (12.3,8.7,0.2)m. For example, the initial coordinates of the midpoint are set to (6.15,4.35,9.5)m. The advantage of this step is that it provides a reasonable starting point for iteration, avoids blind searching, and significantly improves computational efficiency.

[0154] When calculating the internal tension distribution of the guy wire based on the force equilibrium condition, nodal force equilibrium equations are established based on the spatial coordinates of the current iteration. The guy wire is discretized into 50 elements, and force equilibrium equations in three directions are established at each node. For example, at node 25 (near the midpoint of the guy wire), the element direction vector is calculated based on the spatial coordinates of adjacent nodes. Combined with material parameters (elastic modulus 190 GPa, cross-sectional area 100 mm²), the tension value of each node is obtained by solving a system of linear equations. The calculation results show that the initial tension at this node is approximately 1850 N. This step transforms spatial geometric information into mechanical parameters, establishing a quantitative relationship between shape and internal force.

[0155] To verify the matching degree between the actual length of the tension cable under the current tension distribution and the spatial coordinates, a dual verification mechanism is adopted. First, the geometric length based on the spatial coordinates is calculated. By summing the lengths of each discrete segment, the total length of the tension cable under the current configuration is obtained as 22.84m. Simultaneously, the elastic elongation is calculated based on the tension distribution, with the elongation ΔL of each unit being calculated. i =(T i ×L （0，i） The sum of (E×A) / (E×A) yields the actual length, considering elastic deformation, at 22.81m. The difference between the two is 0.03m, exceeding the allowable error range. This verification process ensures the consistency of the model in both geometric and mechanical aspects.

[0156] Among them, L （0，i） It represents the original length of the i-th discrete unit of the pull line.

[0157] When adjusting the iterative values ​​of spatial positions based on the verification results, a gradient-based optimization algorithm is employed. The adjustment amount for the spatial coordinates is calculated based on the length error of 0.03m and its distribution. For example, the midpoint coordinates (6.15, 4.35, 9.5)m are adjusted by 0.12m vertically, becoming (6.15, 4.35, 9.62)m. Simultaneously, the positions of other nodes are adjusted to maintain the smoothness and continuity of the curve. After adjustment, the tension distribution is recalculated, yielding new tension values; the midpoint tension becomes 1820N. This iterative adjustment process gradually corrects the spatial morphology, causing the model to gradually approximate the true state.

[0158] The recalculation and verification steps were repeated, with convergence criteria set as a relative length error of less than 0.1% and a maximum tension change rate of less than 0.5%. After 6 iterations, the difference between the geometric length and the elastic length decreased to 0.002m, the relative error was 0.009%, and the maximum tension change rate was 0.3%, satisfying the convergence criteria. The calculation results were recorded during each iteration to form a convergence curve, ensuring the reliability and traceability of the calculation process.

[0159] When converting the spatial coordinates determined by the final iteration into real-time spatial attitude parameters, the key attitude parameters of the guy wire are calculated based on the converged spatial coordinate data. These include: the overall azimuth of the guy wire (e.g., 35° east of north), the overall tilt angle (e.g., 45°), and the curvature at each point (e.g., 0.15m curvature at the midpoint). -1 The numerical calculation results, along with deformation distribution parameters, are output in a standardized data format to form a complete attitude assessment report. This step transforms the numerical calculation results into engineering-usable attitude parameters, providing a direct basis for condition assessment and early warning.

[0160] Assume the original length L of the wire at unit i=25 is... （0，i） =0.452m, tension T i =1820N, elastic modulus E=190GPa, cross-sectional area A=100mm² 2 Then the elongation ΔL of the unit i =(1820×0.452) / (190×10 9 ×100×10 -6 =0.000043m. The total elongation of all 50 units is summed to obtain a total elongation of 0.00215m, which is compared with the geometric length to verify convergence.

[0161] After the model iteration converges and the spatial coordinate sequence is finally determined, the following specific steps are performed to generate complete real-time spatial attitude parameters:

[0162] Based on the converged spatial coordinate data, the overall geometric attitude parameters of the wire are calculated, including the overall azimuth, overall tilt angle and actual spatial arc length.

[0163] Extract the mechanical and deformation parameters of the draw wire, including tension distribution, deformation distribution, and curvature distribution;

[0164] The overall geometric attitude parameters and mechanical and deformation parameters are integrated according to a preset standardized data format to generate an attitude evaluation report.

[0165] In practice, based on the converged spatial coordinate sequence, the overall geometric attitude of the guy wire is first calculated. The overall azimuth is obtained by calculating the direction of the line connecting the first and last ends of the guy wire's projection onto the horizontal plane. Based on the projected coordinates of the upper fixed point (0,0) and the lower fixed point (12.3,8.7), the azimuth is calculated using the arctangent function as arctan(8.7 / 12.3)≈35.3°, which is recorded as "35.3° east of north". The overall tilt is obtained by calculating the angle between the spatial vector connecting the two ends of the guy wire and the horizontal plane. The spatial vector coordinates are (12.3,8.7,-18.3), and the horizontal projection length is sqrt(12.3). 2 +8.7 2 If the length is approximately 15.1m, then the overall tilt angle is approximately arctan(18.3 / 15.1)≈50.5°. The actual spatial arc length is calculated by summing the lengths of the 50 converged discrete units, resulting in a total spatial length of 22.838 meters for the tensioned wire, including its elastic elongation.

[0166] Based on the output of the converged mechanical model, key mechanical and deformation parameters are extracted. Tension distribution directly outputs the steady-state tension values ​​of each node after iterative convergence, forming a complete tension distribution list. The steady-state tension at the midpoint (node ​​25) is explicitly recorded as 1820N, and the maximum tension of 1850N, occurring near node 10, is identified. Deformation distribution calculates the spatial deformation of each node by comparing the converged node coordinates with the initial design shape of the guy wire. The vertical deformation at the midpoint is recorded as +0.12m, representing a 0.12-meter sag relative to the initial shape. Curvature distribution calculates the curvature values ​​of each point based on the spatial coordinate sequence, with the midpoint curvature calculated as 0.15m. -1 .

[0167] All calculated attitude parameters are integrated according to a pre-defined standardized data structure to generate a complete attitude assessment report. The report employs a hierarchical data structure: the top layer contains basic information and overall geometric parameters; the middle layer contains mechanical state parameters; and the bottom layer contains detailed deformation distribution and convergence status. Specific report content includes timestamps, guy wire identifiers, overall azimuth angle, overall tilt angle, actual spatial arc length, tension distribution list, maximum tension value and its location, deformation distribution data, curvature distribution data, and convergence status indicators. This standardized data organization facilitates subsequent data retrieval, historical comparison, and status assessment, providing complete and accurate data support for the safety monitoring of pole guy wires. This implementation method achieves a closed-loop technology from multi-sensor data acquisition to complete spatial attitude parameter output, ensuring the accuracy of monitoring results and engineering practicality.

[0168] See Figure 4 In this embodiment, the method further includes the following steps:

[0169] Compare real-time spatial attitude parameters with a preset safety threshold range;

[0170] When the real-time spatial attitude parameters exceed the safety threshold range, a preset pull-wire status warning message is generated;

[0171] Based on the type and level of the cable status warning information, corresponding maintenance decision suggestions are output.

[0172] In practical implementation, the first step is to establish a complete safety threshold database. This database contains the safety threshold ranges for various attitude parameters of the guy wire, which are determined comprehensively based on design specifications, historical data, and operational experience. For example, for the guy wire tilt angle, the first-level safety threshold is set to ±5° of the design value, the second-level safety threshold to ±8°, and the third-level safety threshold to ±10°; for the guy wire tension, a safety factor of no less than 2.5 is set, corresponding to a maximum allowable tension of 40% of the breaking tension; for deformation, the relative deformation is set to not exceed 0.3% of the original length. These thresholds are categorized and stored according to guy wire type, operating environment, and service life, and are periodically revised based on actual conditions.

[0173] During the actual comparison process, the system reads the calculated spatial attitude parameters in real time, including the overall tilt angle, azimuth angle, tension distribution at each point, and deformation. Taking the GJ-100 type guy wire of a certain tower as an example, the system monitors that the overall tilt angle of the guy wire has reached 52°, exceeding the secondary safety threshold of 50°; at the same time, the tension at the midpoint of the guy wire has reached 12.5kN, exceeding the breaking tension (25kN) by 50%, exceeding the tertiary safety threshold. The system automatically compares these measured values ​​with the corresponding parameters in the safety threshold database, recording the name of the parameter exceeding the threshold, the magnitude of the exceedance, and the duration.

[0174] When spatial attitude parameters are detected to exceed safety thresholds, the system generates tiered warning messages based on the degree of exceedance and the importance of the parameters. Warnings are categorized into three levels: general warning (yellow), moderate warning (orange), and severe warning (red). For example, a general warning is generated when only one minor parameter slightly exceeds the threshold; a moderate warning is generated when a critical parameter such as tension or tilt angle exceeds the secondary threshold; and a severe warning is generated when multiple critical parameters simultaneously exceed the threshold or a single parameter exceeds the tertiary threshold. The warning information includes the specific parameter exceeding the limit, the value exceeding the limit, the time of occurrence, and the suggested processing time.

[0175] Based on the type and level of the warning information, the system outputs corresponding maintenance decision suggestions. The maintenance decision suggestion library contains detailed handling solutions for different warning situations. For a general warning of excessive tilt angle, it is recommended to "arrange an inspection within 15 days to check the guy wire hardware and anchor points"; for a more severe warning of excessive tension, it is recommended to "conduct on-site testing within 72 hours and adjust the tension if necessary"; for a serious warning of excessive multiple parameters, it is recommended to "immediately take temporary reinforcement measures and carry out emergency repairs within 24 hours". The system will also provide targeted maintenance solutions based on historical warning records and trend analysis, such as "the tension of this guy wire has been rising continuously for the past three months, and it is recommended to focus on checking for corrosion".

[0176] The advantage of this implementation method lies in establishing a complete early warning and maintenance decision-making system, which can promptly detect abnormal conditions in guy wires and provide targeted handling suggestions, effectively preventing accidents. Through a tiered early warning mechanism, it ensures timely handling of serious hidden dangers while avoiding resource waste caused by excessive maintenance. Actual operation shows that this early warning system can detect the development trend of abnormal guy wire conditions 24-72 hours in advance, providing ample preparation time for maintenance work and significantly improving the safety and reliability of power grid operation.

[0177] The second embodiment of the present invention provides a method and system for monitoring the attitude of utility pole guy wires based on multi-sensor data fusion, used to execute a method for monitoring the attitude of utility pole guy wires based on multi-sensor data fusion. The system includes:

[0178] The data acquisition module is configured to acquire raw monitoring data collected by multiple sensors installed on the guy wire of the utility pole, the raw monitoring data including angle data and displacement data of the guy wire;

[0179] The standardization processing module is configured to perform standardization processing on the original monitoring data to generate standardized data with a unified spatiotemporal reference.

[0180] The dataset construction module is configured to combine the standardized data according to preset physical quantity association rules to construct a comprehensive dataset containing angular and displacement features.

[0181] The multi-source fusion computing module is configured to perform multi-source data fusion computing on the comprehensive dataset. It utilizes the synergistic relationship between the orientation measurement characteristics of angle data and the deformation measurement characteristics of displacement data to generate feature data describing the comprehensive spatial state of the guy wire through a weighted fusion algorithm. The feature data includes the position and shape information of the guy wire in three-dimensional space.

[0182] The spatial attitude calculation module is configured to input the feature data into the pole guy wire mechanical analytical model, and obtain the real-time spatial attitude parameters of the pole guy wire by solving the mechanical analytical model. The pole guy wire mechanical analytical model is established based on the force balance condition and geometric constraint relationship of the guy wire. The mechanical analytical model solves the spatial attitude of the guy wire by establishing the correspondence between tension distribution and spatial coordinates.

[0183] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process and related explanations of the methods described above can be found in the corresponding processes in the foregoing system embodiments, and will not be repeated here.

[0184] It should be noted that the pole guy wire attitude monitoring method system based on multi-sensor data fusion provided in the above embodiments is only an example of the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the modules or steps in the embodiments of the present invention can be further decomposed or combined. For example, the modules in the above embodiments can be merged into one module, or further divided into multiple sub-modules to complete all or part of the functions described above. The names of the modules and steps involved in the embodiments of the present invention are only for distinguishing the various modules or steps and are not considered as an improper limitation of the present invention.

[0185] A device according to a third embodiment of the present invention includes:

[0186] At least one processor;

[0187] and a memory communicatively connected to at least one of the processors;

[0188] The memory stores instructions that can be executed by the processor to implement the above-described method for monitoring the attitude of guy wires on utility poles based on multi-sensor data fusion.

[0189] A computer-readable storage medium according to a fourth embodiment of the present invention stores computer instructions, which are executed by the computer to implement the above-described method for monitoring the attitude of guy wires on utility poles based on multi-sensor data fusion.

[0190] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process and related descriptions of the storage device and processing device described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0191] The following is for reference. Figure 5 It shows a schematic diagram of the structure of a computer system for implementing embodiments of the systems, methods, and electronic devices of this application. Figure 5 The server shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0192] like Figure 5 As shown, the computer system includes a Central Processing Unit (CPU) 501, which can perform various appropriate actions and processes based on programs stored in Read Only Memory (ROM) 502 or programs loaded from storage section 508 into Random Access Memory (RAM) 503. The RAM 503 also stores various programs and data required for system operation. The CPU 501, ROM 502, and RAM 503 are interconnected via a bus 504. An Input / Output (I / O) interface 505 is also connected to the bus 504.

[0193] The following components are connected to I / O interface 505: an input section 506 including a keyboard, mouse, etc.; an output section 507 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to I / O interface 505 as needed. Removable media 511, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 510 as needed so that computer programs read from them can be installed into storage section 508 as needed.

[0194] Specifically, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 509, and / or installed from removable medium 511. When the computer program is executed by central processing unit (CPU) 501, it performs the functions defined in the methods of this application. It should be noted that the computer-readable medium described above in this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on a computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0195] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0196] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0197] The terms “first”, “second”, etc., are used to distinguish similar objects, not to describe or indicate a specific order or sequence.

[0198] The term "comprising" or any other similar term is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus / device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent in such process, method, article, or apparatus / device.

[0199] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A method for monitoring the posture of a pole guy based on multi-sensor data fusion, comprising: obtaining raw monitoring data collected by a plurality of sensors arranged on the pole guy, including angle data and displacement data of the guy; standardizing the raw monitoring data to generate standardized data with a unified space-time reference; combining the standardized data according to a pre-set physical quantity correlation rule to construct a comprehensive data set containing angle characteristic quantities and displacement characteristic quantities; performing multi-source data fusion calculation on the comprehensive data set, using the collaborative relationship between the azimuth measurement characteristics of the angle data and the deformation measurement characteristics of the displacement data, and generating characteristic data describing the comprehensive spatial state of the guy through a weighted fusion algorithm, the characteristic data containing position information and shape information of the guy in three-dimensional space; inputting the characteristic data into a mechanical analysis model to obtain real-time spatial posture parameters of the pole guy by solving the mechanical analysis model, the mechanical analysis model being established based on the force balance condition and geometric constraint relationship of the guy, and the spatial posture of the guy being solved by establishing the correspondence between the tension distribution and the spatial coordinates; the method for establishing the mechanical analysis model comprising: establishing a spatial rectangular coordinate system of the pole guy to determine the spatial coordinates of the fixed points at both ends of the guy; obtaining material characteristic parameters and structural parameters of the guy; establishing a force balance equation set of the internal tension of the guy and the external load based on the structural parameters; establishing a geometric constraint equation set of the spatial position and length variation of the guy based on the coordinates of the fixed points at both ends of the guy and the actual length of the guy; combining the force balance equation set and the geometric constraint equation set to construct a mathematical relationship between the spatial position and the tension distribution of the guy; converting the mathematical relationship into an operation model that can calculate the posture parameters by inputting the characteristic data through a numerical calculation method; solving the spatial posture of the guy by establishing the correspondence between the tension distribution and the spatial coordinates, comprising: setting an initial iteration value of the spatial position of the guy based on the input characteristic data; calculating the internal tension distribution of the guy corresponding to the current spatial position according to the force balance condition; verifying the matching degree of the actual length of the guy and the spatial coordinates under the current tension distribution according to the geometric constraint relationship; adjusting the iteration value of the spatial position based on the verification result, recalculating the internal tension distribution of the guy corresponding to the adjusted spatial position, and verifying the matching degree of the actual length of the guy and the spatial coordinates again; repeating the recalculating and verifying steps until a pre-set convergence condition is met; converting the spatial coordinates finally determined by iteration into real-time spatial posture parameters of the pole guy.

2. The method according to claim 1, wherein The method for performing multi-source data fusion calculation on the comprehensive data set comprises: extracting angle characteristic quantities and displacement characteristic quantities from the comprehensive data set respectively; obtaining the measurement error range of the angle sensor measured under a standard test environment and the measurement error range of the displacement sensor measured under a standard test environment; assigning a first weight coefficient to the angle characteristic quantities based on the measurement error range, and assigning a second weight coefficient to the displacement characteristic quantities based on the measurement error range, wherein the measurement error range is inversely proportional to the weight coefficient assigned to the sensor data; The angle characteristic quantity and the displacement characteristic quantity are fused and calculated by weighting using the first weight coefficient and the second weight coefficient, to obtain position information of the stay wire in a three-dimensional space; Based on the position information and deformation measurement data in the displacement characteristic quantity, feature data describing the comprehensive spatial state of the stay wire is generated.

3. The method according to claim 2, wherein, Based on the position information and deformation measurement data in the displacement characteristic quantity, feature data describing the comprehensive spatial state of the stay wire is generated, and the method comprises the steps of: determining a reference shape of the stay wire in a three-dimensional space according to the position information; combining the deformation measurement data in the displacement characteristic quantity to calculate a spatial deformation variable of the stay wire relative to the reference shape; determining an actual spatial shape parameter of the stay wire based on the spatial deformation variable and the reference shape; combining the position information and the spatial shape parameter according to a preset data structure, wherein the position information serves as a spatial reference, and the spatial shape parameter serves as a shape feature description, to jointly constitute the feature data.

4. The method of claim 1, wherein the method is based on multi-sensor data fusion. The material characteristic parameters include an elastic modulus and a material density, and the structure parameters include an original length and a cross-sectional area; and the external load includes a self-weight load and an environmental load. The numerical calculation method comprises establishing a discretized calculation model and configuring an iterative calculation algorithm.

5. The method of claim 1, wherein the method is based on multi-sensor data fusion for monitoring the posture of the electric pole. The standardized data is combined according to a preset physical quantity correlation rule to construct a comprehensive data set containing the angle characteristic quantity and the displacement characteristic quantity, and the method comprises the steps of: classifying the standardized data according to the physical quantity types thereof, assigning an angle characteristic quantity identifier to angle data, and assigning a displacement characteristic quantity identifier to displacement data; correlating the angle characteristic quantity and the displacement characteristic quantity having the same time reference and spatial reference according to the time stamp information and the spatial coordinate information carried in the standardized data; performing data integrity checking on the correlated angle characteristic quantity and displacement characteristic quantity to ensure that the angle characteristic quantity and the displacement characteristic quantity at each time point are completely corresponding; organizing the angle characteristic quantity and the displacement characteristic quantity that pass the integrity checking according to a time sequence to construct the comprehensive data set.

6. The method of claim 1, wherein the method is based on multi-sensor data fusion. The method further comprises the following steps: comparing the real-time spatial attitude parameter with a preset safety threshold range; generating a preset stay wire state warning information when the real-time spatial attitude parameter exceeds the safety threshold range; outputting a corresponding maintenance decision suggestion according to the type and level of the stay wire state warning information.

7. The method of claim 1, wherein the method is based on multi-sensor data fusion. The sensors comprise angle sensors and displacement sensors, and the angle sensors and the displacement sensors are arranged at a preset interval along the length direction of the pole stay wire.

8. A method system for pole guying posture monitoring based on multi-sensor data fusion, for performing the method of any one of claims 1-7, characterized in that, The system comprises: a data acquisition module configured to acquire original monitoring data collected by a plurality of sensors arranged on the pole stay wire, including angle data and displacement data of the stay wire; a standardization processing module configured to perform standardization processing on the original monitoring data to generate standardized data having a unified time and space reference; a data set construction module configured to combine the standardized data according to a preset physical quantity correlation rule to construct a comprehensive data set containing the angle characteristic quantity and the displacement characteristic quantity; and a data set construction module configured to combine the standardized data according to a preset physical quantity correlation rule to construct a comprehensive data set containing the angle characteristic quantity and the displacement characteristic quantity. The multi-source fusion computing module is configured to perform multi-source data fusion computation on the comprehensive data set, utilize the synergistic relationship between the azimuth measurement characteristic of the angle data and the deformation measurement characteristic of the displacement data, and generate feature data describing the comprehensive spatial state of the pull wire through a weighted fusion algorithm. The feature data includes position information and shape information of the pull wire in a three-dimensional space. The spatial attitude computing module is configured to obtain real-time spatial attitude parameters of the electric pole pull wire by solving a mechanical analysis model. The mechanical analysis model is established based on force balance conditions and geometric constraint relationships of the pull wire, and the spatial attitude of the pull wire is solved by establishing a corresponding relationship between tension distribution and spatial coordinates.

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