Power tower settlement posture monitoring method, system, device and storage medium

Abstract

The present application relates to a power tower settlement posture monitoring method, system, device and storage medium. The current method for evaluating the actual stability state of the tower is relatively single. The present application comprises obtaining the first posture information of the target tower at the current time, generating the first stability score of the target tower; generating the first environmental influence coefficient of the target tower within the first preset time length; generating the second environmental influence coefficient of the associated tower within the first preset time length; generating the associated influence coefficient of the target tower; generating the posture natural change amount of the target tower within the first preset time length; generating the second stability score of the target tower, adjusting the second stability score, generating the target stability score, and generating the warning information when the target stability score is lower than the preset score. The present application not only considers the state of the tower itself, but also includes environmental conditions, associated influences and natural changes and other multi-dimensional influencing factors, which can more accurately reflect the actual stability state of the tower.

Description

Technical Field

[0001] This invention relates to the field of power equipment monitoring technology, specifically to methods, systems, equipment, and storage media for monitoring the settlement attitude of power poles. Background Technology

[0002] The stability of transmission line towers is directly related to the safe operation of the power system. Due to factors such as natural disasters and changes in geological conditions, towers may settle or tilt. If these issues are not detected and addressed in a timely manner, they could lead to serious accidents such as transmission line breakage or tower collapse. Therefore, real-time monitoring of tower settlement and attitude changes, and timely detection of potential risks, is of great significance for ensuring the safe operation of the power grid.

[0003] Currently, the common practice is to install tilt sensors and displacement sensors on the towers to collect real-time attitude data such as the tower's tilt angle and settlement, and then determine the tower's stability based on this data. However, this method only considers the tower's own attitude changes. Under complex geological conditions, the stability of the tower is often affected by a combination of factors, and relying solely on single attitude data is insufficient to accurately assess the tower's actual stability.

[0004] Therefore, there is an urgent need for a method to monitor the settlement attitude of power poles that can accurately assess the actual stability of the poles. Summary of the Invention

[0005] The purpose of this invention is to provide a method, system, device, and storage medium for monitoring the settlement attitude of power poles, so as to at least solve the problem of limited data in current methods for assessing the actual stability of poles.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] A method for monitoring the settlement attitude of power poles, the monitoring method comprising:

[0008] Obtain the first attitude information of the target tower at the current moment, and generate the first stability score of the target tower based on the first attitude information;

[0009] The first geographical feature of the target tower's location and the first environmental information of the target tower within a first preset time period after the current time are obtained. The first environmental impact coefficient of the target tower within the first preset time period is generated by combining the first geographical feature and the first environmental information.

[0010] Obtain the second geographical features of the location of the associated towers associated with the target tower, and the second environmental information of the associated towers within the first preset time period. Combine the second geographical features and the second environmental information to generate the second environmental impact coefficient of the associated towers within the first preset time period.

[0011] By combining the second environmental impact coefficient and the second attitude information of the associated tower, the associated impact coefficient of the target tower is generated;

[0012] Obtain the attitude change data of the target tower within a second preset time period before the current moment, and generate the natural attitude change amount of the target tower within the first preset time period based on the attitude change data;

[0013] The first stability score is adjusted based on the natural attitude change amount to generate a second stability score for the target tower. The second stability score is then adjusted based on the correlation influence coefficient and the first environmental influence coefficient to generate a target stability score. When the target stability score is lower than a preset score, an early warning message is generated.

[0014] Furthermore, the step of combining the first geographical feature and the first environmental information to generate the first environmental impact coefficient of the target tower within the first preset time period includes:

[0015] Determine the geological influence coefficient corresponding to the geological type of the first geographical feature from the preset geological influence coefficient comparison table;

[0016] Substitute the slope of the first geographical feature into the first preset formula to calculate the slope influence coefficient;

[0017] Multiply the geological influence coefficient by the slope influence coefficient to generate the target geological influence coefficient;

[0018] By combining the target geological influence coefficient and the first environmental information, a first environmental influence coefficient for the target tower within the first preset time period is generated.

[0019] Furthermore, the step of combining the target geological influence coefficient and the first environmental information to generate the first environmental influence coefficient of the target tower within the first preset time period includes:

[0020] Based on the first environmental information, determine the average soil moisture value of the target tower location within the first preset time period;

[0021] Substitute the average soil moisture value into the second preset formula to calculate the soil moisture influence coefficient;

[0022] The target geological influence coefficient and the soil moisture influence coefficient are weighted and summed to generate the first environmental influence coefficient of the target tower within the first preset time period.

[0023] Furthermore, the step of generating the correlation influence coefficient of the target tower by combining the second environmental influence coefficient and the second attitude information of the associated tower includes:

[0024] Obtain the distance information between the associated tower and the target tower;

[0025] Based on the distance information, the corresponding distance attenuation coefficient is determined from a preset distance influence coefficient lookup table;

[0026] A second stability score for the associated tower is generated based on the second attitude information of the associated tower.

[0027] Substituting the second stability score of the associated tower, the second environmental impact coefficient, and the distance attenuation coefficient into the third preset formula, the associated impact coefficient of the target tower is generated.

[0028] Furthermore, adjusting the first stability score based on the natural attitude change to generate a second stability score for the target tower includes:

[0029] Based on the natural change in attitude, the predicted attitude offset of the target tower within the first preset time period is determined;

[0030] A correction factor is generated based on the predicted attitude offset.

[0031] The correction factor is multiplied by the first stability score to generate the second stability score.

[0032] Furthermore, the adjustment of the second stability score by combining the correlation influence coefficient and the first environmental influence coefficient to generate a target stability score includes:

[0033] Substitute the correlation influence coefficient into the fourth preset formula to calculate the correlation adjustment factor;

[0034] The correlation adjustment factor is multiplied by the second stability score to generate a third stability score;

[0035] Based on the first environmental impact coefficient, the third stability score is adjusted to generate the target stability score.

[0036] Furthermore, the step of adjusting the third stability score based on the first environmental impact coefficient to generate the target stability score includes:

[0037] Substitute the first environmental impact coefficient into the fifth preset formula to calculate the environmental adjustment factor;

[0038] The target stability score is generated by multiplying the environmental adjustment factor by the third stability score.

[0039] A power pole settlement attitude monitoring system, the monitoring system comprising:

[0040] The first acquisition module is used to acquire the first attitude information of the target tower at the current moment, and generate the first stability score of the target tower based on the first attitude information.

[0041] The second acquisition module is used to acquire the first geographical features of the location of the target tower and the first environmental information of the target tower within a first preset time after the current time, and to generate the first environmental impact coefficient of the target tower within the first preset time by combining the first geographical features and the first environmental information.

[0042] The third acquisition module is used to acquire the second geographical features of the location of the associated tower associated with the target tower, and the second environmental information of the associated tower within the first preset time period. Combining the second geographical features and the second environmental information, a second environmental impact coefficient of the associated tower within the first preset time period is generated.

[0043] The module is used to combine the second environmental impact coefficient and the second attitude information of the associated tower to generate the associated impact coefficient of the target tower;

[0044] The fourth acquisition module is used to acquire the attitude change data of the target tower within a second preset time period before the current moment, and generate the natural attitude change amount of the target tower within the first preset time period based on the attitude change data.

[0045] The adjustment module is used to adjust the first stability score according to the natural change in attitude, generate a second stability score for the target tower, and adjust the second stability score in combination with the correlation influence coefficient and the first environmental influence coefficient to generate a target stability score. When the target stability score is lower than the preset score, an early warning message is generated.

[0046] An electronic device includes a processor, a memory, a user interface, and a network interface. The memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory to cause the electronic device to perform the method described in any of the above.

[0047] A computer-readable storage medium storing a computer program that can be loaded by the processor and execute the method described in any of the preceding methods.

[0048] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0049] This invention provides a method, system, device, and storage medium for monitoring the settlement attitude of power poles. It generates an initial stability score by acquiring the target pole's attitude information and then generates an environmental impact coefficient by combining geographical features and environmental information. It also considers the influencing factors of related poles and analyzes natural variation patterns based on historical attitude change data. Finally, it obtains the target stability score through multi-level scoring adjustments. This comprehensive evaluation method not only considers the pole's own state but also includes multiple dimensions of influencing factors such as environmental conditions, related influences, and natural variations. It can more accurately reflect the actual stability state of the pole. By triggering an early warning mechanism through a preset scoring threshold, potential risks can be detected in a timely manner, providing reliable decision-making basis for maintenance personnel, effectively reducing the probability of false alarms and missed alarms, and accurately assessing the actual stability state of the pole. Attached Figure Description

[0050] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other embodiments can be obtained from these drawings without creative effort.

[0051] Figure 1 This is a flowchart of Example 1;

[0052] Figure 2 This is a structural schematic diagram of Example 3;

[0053] The diagram is labeled as follows:

[0054] 1-Processor, 2-Communication bus, 3-User interface, 4-Network interface, 5-Memory. Detailed Implementation

[0055] To facilitate understanding of the present invention, a more complete description will be given below with reference to the accompanying drawings. Preferred embodiments of the invention are shown in the drawings. However, the invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a thorough and complete understanding of the disclosure of the invention.

[0056] It should be noted that similar reference numerals and letters indicate similar items; therefore, once an item is defined in one embodiment, it does not need to be further defined and explained in subsequent embodiments. Furthermore, the terms "comprising" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0057] It should also be noted that although the order of steps is mentioned in the method description, in some cases, steps may be performed in a different order than that described here, and this should not be interpreted as a restriction on the order of steps.

[0058] Example 1:

[0059] This embodiment provides a method for monitoring the settlement attitude of power poles, including the following steps:

[0060] S1: Obtain the first attitude information of the target tower at the current moment, and generate the first stability score of the target tower based on the first attitude information.

[0061] First, the initial attitude information of the target tower is acquired using attitude sensors installed on the tower. This initial attitude information includes the tower's tilt angle and settlement depth. The tilt angle is measured using a gyroscope sensor (model JY901S); the settlement depth is obtained using a barometric altimeter (model BMP280) combined with a differential calculation method. The settlement displacement value is calculated by comparing the currently measured altitude with the initial altitude at the time of tower installation.

[0062] After obtaining the first attitude information, the stability state of the target tower is quantitatively evaluated.

[0063] Specifically, the tilt angle value is first substituted into the preset angle-score mapping function. Obtain the tilt score Simultaneously, the settlement depth value is substituted into the preset settlement-score mapping function. Settlement score obtained , where the mapping function and The piecewise function is derived from statistical analysis of a large amount of historical data. Different calculation parameters are used for different intervals to more accurately reflect the degree of influence of attitude changes on tower stability.

[0064] Then, the tilt weight is determined based on the type of the target tower (straight-line tower, tension tower, etc.) and its height level. and settlement weight The first stability score is obtained by weighted summation of the two scores. The scoring system uses a 100-point scale, with higher scores indicating greater tower stability. The advantages of this scoring mechanism are: firstly, standardization makes different types of attitude data comparable; secondly, the introduction of weights makes the scoring more consistent with the actual conditions of different types of towers; and finally, the 100-point scale is more intuitive, facilitating subsequent early warning assessments.

[0065] S2: Obtain the first geographical feature of the target tower's location and the first environmental information of the target tower within a first preset time period after the current time. Combine the first geographical feature and the first environmental information to generate the first environmental impact coefficient of the target tower within the first preset time period.

[0066] The primary geographical features include: geological type and slope. The geological type is obtained through geological survey reports and verified with reference to the national geological information database; the slope is obtained through high-precision GPS and laser rangefinder measurements.

[0067] S201: Determine the geological influence coefficient corresponding to the geological type of the first geographical feature from the preset geological influence coefficient comparison table.

[0068] The preset geological influence coefficient comparison table includes: multiple geological types and their corresponding geological influence coefficients.

[0069] The coefficient values ​​in the reference table are determined based on statistical analysis of a large amount of historical data, reflecting the degree of influence of different geological conditions on the stability of the tower. The geological influence coefficient corresponding to the geological type of the target tower can be found in the reference table as the basic parameter for subsequent calculations.

[0070] S202: Substitute the slope of the first geographical feature into the first preset formula to calculate the slope influence coefficient.

[0071] The first preset formula is: ,

[0072] Where: K is the slope influence coefficient, and b is the basic coefficient (usually taken as 1). For actual slope measurement, The preset benchmark slope (usually 5 degrees) is used. The slope coefficient is taken as 0.02 based on experience.

[0073] The base coefficient b is set to 1, representing the degree of influence under the baseline condition. Choosing 1 as the baseline value is for two reasons: first, it is easy to understand, indicating that it will not have an additional impact on stability under standard conditions; second, it is convenient for subsequent adjustments, as the actual slope can be easily increased or decreased when it deviates from the preset value.

[0074] Use in formula The term represents the deviation between the actual slope and the preset slope, where the preset slope is... The choice of 5 degrees is based on extensive engineering experience. This angle is considered a relatively safe slope for tower construction. When the actual slope is greater than 5 degrees, the deviation is positive, indicating an increase in adverse effects; when the actual slope is less than 5 degrees, the deviation is negative, indicating a reduction in adverse effects.

[0075] Slope coefficient This is a key adjustment parameter that determines the sensitivity of slope changes to the influence coefficient. Setting... This value effectively reflects the actual impact of slope changes on tower stability. The selection of this value takes into account the following factors: the influence coefficient increases by 0.02 for every 1 degree increase in slope, and this rate of change is consistent with the observed downward trend in stability; this coefficient neither overemphasizes nor underemphasizes the influence of slope; and this value facilitates engineering calculations and avoids overly complex decimals.

[0076] S203: The geological influence coefficient and the slope influence coefficient are arithmetically multiplied to generate the target geological influence coefficient.

[0077] S204: Combine the target geological influence coefficient and the first environmental information to generate the first environmental influence coefficient of the target tower within the first preset time period.

[0078] By subdividing geographical features into two specific indicators—geological type and slope—and using a geological influence coefficient comparison table and a slope influence calculation formula to quantify their degree of influence, the assessment of geographical features becomes more precise. The calculation method for the slope influence coefficient considers the basic conditions, the deviation between the actual slope and the standard slope, and the rate of change, which can accurately reflect the impact of different slope conditions on the stability of the tower. By combining the influencing factors of geology and slope to obtain a comprehensive geological influence index, and then combining it with environmental information to generate an environmental influence coefficient, the refined quantification of the impact on the geographical environment is achieved, improving the accuracy and scientific nature of environmental impact assessment.

[0079] Specifically, by combining the target geological influence coefficient and the first environmental information, the first environmental influence coefficient of the target tower within the first preset time period is generated, including:

[0080] S2041: Based on the first environmental information, determine the average soil moisture value of the target tower location within a first preset time period.

[0081] The primary environmental information mainly includes weather forecast data for the first preset time period (usually set to 72 hours), including meteorological elements such as rainfall, wind speed, and temperature. This data is acquired in real time through the meteorological department's forecast interface. Of particular importance is the soil moisture data, which is monitored in real time by humidity sensors buried around the pole foundation.

[0082] S2042: Substitute the average soil moisture value into the second preset formula to calculate the soil moisture influence coefficient.

[0083] The second preset formula is: ,

[0084] Where: M is the soil moisture influence coefficient, d is the baseline coefficient (value 1.0), and H is the average soil moisture during the prediction period. The preset soil moisture threshold is (usually 30%). The soil moisture influencing factor (value 0.015).

[0085] S2043: The target geological influence coefficient and the soil moisture influence coefficient are weighted and summed to generate the first environmental influence coefficient of the target tower within the first preset time period.

[0086] By acquiring soil moisture data at the location of the target tower and calculating the average value over the prediction period, a specialized calculation method is used to quantify the impact of soil moisture on tower stability. This calculation method comprehensively considers the baseline conditions, the deviation between the actual soil moisture and the standard threshold, and the degree of impact, which can accurately reflect the impact of soil moisture changes on tower stability. By weighting the impact of soil moisture with the aforementioned geological impacts, the final environmental impact coefficient is generated, realizing differentiated processing of the impact of different environmental factors, making the environmental impact assessment more comprehensive and accurate, and effectively improving the reliability of tower stability assessment.

[0087] S3: Obtain the second geographical features of the location of the associated towers associated with the target tower, and the second environmental information of the associated towers within a first preset time period. Combine the second geographical features and the second environmental information to generate the second environmental impact coefficient of the associated towers within the first preset time period.

[0088] In this embodiment, the towers on the transmission line are interconnected by conductors to form a whole system. Any change in the stability of any tower may affect the adjacent towers through the transmission of conductor tension. Therefore, it is necessary to consider the potential impact of the environmental conditions of the associated towers on the target tower. Associated towers usually refer to adjacent towers that are directly connected to the target tower. Under special terrain conditions, it may also be necessary to consider the impact of the next adjacent tower.

[0089] S4: Combine the second environmental impact coefficient and the second attitude information of the associated tower to generate the associated impact coefficient of the target tower.

[0090] In this embodiment, in the mechanical coupling system formed by the connection of power poles through conductors, the stability of the associated poles will affect the target pole through the transmission of conductor tension. The degree of this influence is not only related to the environmental conditions of the associated poles, but also closely related to their own attitude and spatial position. Therefore, it is necessary to comprehensively consider these factors and quantify the associated influence into an associated influence coefficient through scientific calculation methods.

[0091] S401: Obtain distance information between the associated tower and the target tower.

[0092] First, the system obtains the precise distance information between the associated tower and the target tower through GPS positioning and ranging equipment. This distance is the basic parameter for assessing the association effect, because the transmission strength of the effect usually decreases with increasing distance. The system has a preset distance effect coefficient reference table. The corresponding distance attenuation coefficient can be looked up from the table according to the measured distance. This reference table is based on the statistical analysis of a large amount of engineering data and reflects the attenuation law of the association effect at different distances.

[0093] S402: Based on the distance information, determine the corresponding distance attenuation coefficient from the preset distance influence coefficient reference table.

[0094] S403: Generate the second stability score of the associated tower based on the second attitude information of the associated tower.

[0095] Simultaneously, the system needs to assess the stability of the associated towers. By analyzing the second attitude information of the associated towers (including tilt angle, settlement, etc.), and according to the same scoring standard as the target tower, a second stability score of the associated towers is generated. This score reflects the current stability of the associated towers and is an important input parameter for calculating the associated impact.

[0096] S404: Substitute the second stability score, second environmental impact coefficient, and distance attenuation coefficient of the associated tower into the third preset formula to generate the associated impact coefficient of the target tower.

[0097] The third preset formula is: ,

[0098] Where: R is the correlation influence coefficient, μ is the correlation benchmark coefficient (usually taken as 1), S is the stability score of the correlated tower, E is the second environmental influence coefficient, λ is the distance attenuation factor (usually taken as 0.005), and D is the distance between the correlated tower and the target tower.

[0099] By acquiring distance information between associated towers and the target tower and introducing a distance attenuation coefficient, and combining the stability score and environmental impact coefficient of the associated towers, a calculation method considering distance attenuation characteristics is adopted to quantify the associated impact. This method not only considers the stability state and environmental conditions of the associated towers themselves, but also reasonably controls the transmission attenuation of the impact intensity through a benchmark coefficient and a distance attenuation factor, making the assessment of the associated impact more in line with actual laws. This associated impact assessment method based on multi-factor coupling can accurately reflect the actual impact of changes in the state of associated towers on the target tower, and improves the accuracy of the stability assessment of the tower group.

[0100] S5: Obtain the attitude change data of the target tower within the second preset time period before the current moment, and generate the natural attitude change amount of the target tower within the first preset time period based on the attitude change data.

[0101] In this embodiment, the attitude changes of power poles usually exhibit a certain degree of gradualness and regularity. By analyzing historical data, future trends can be predicted. Accurate prediction of this natural trend is crucial for assessing the stability of the poles, as it reflects the direction and rate of the poles' evolution when there are no external sudden factors interfering.

[0102] S6: Adjust the first stability score based on the natural change in attitude to generate the second stability score of the target tower. Combine the correlation influence coefficient and the first environmental influence coefficient to adjust the second stability score and generate the target stability score. When the target stability score is lower than the preset score, generate an early warning message.

[0103] In this embodiment, in order to obtain more accurate tower stability assessment results, the initial first stability score needs to be adjusted in multiple levels, taking into account the effects of natural change trends, related influences and environmental factors. This step-by-step adjustment method can more comprehensively reflect the actual stability state of the tower and provide more reliable early warning basis.

[0104] S601: Determine the predicted attitude offset of the target tower within the first preset time period based on the natural attitude change amount.

[0105] The system first uses time series analysis based on historical monitoring data to identify the natural variation patterns in the tower's attitude changes. These natural variations include periodic changes caused by diurnal temperature differences, seasonal changes, and gradual processes such as slow foundation settlement. By analyzing these natural variation patterns and combining them with current monitoring data, the system can predict the natural attitude change trend of the target tower within a first preset time period (72 hours), thereby determining the predicted attitude offset.

[0106] S602: Generate a correction factor based on the predicted attitude offset.

[0107] The prediction of attitude offset is calculated using a multinomial regression model, which takes into account both periodic and trend changes in historical data. The system uses this model to calculate the expected attitude change in the next 72 hours, which reflects the natural evolution of the tower's attitude under normal conditions.

[0108] The correction factor is negatively correlated with the predicted attitude offset. This design is based on the following considerations: when the predicted natural offset is large, it indicates that the currently observed attitude change may mainly be caused by natural factors, and the actual stability risk is relatively small; when the predicted natural offset is small, it indicates that the currently observed attitude change may mainly be caused by non-natural factors, and more attention needs to be paid to potential risks.

[0109] The correction factor is calculated using normalization and typically ranges from 0.8 to 1.2. When the predicted attitude offset is greater than the historical average, the correction factor is less than 1, indicating an appropriate reduction in the risk assessment level; when the predicted attitude offset is less than the historical average, the correction factor is greater than 1, indicating an increase in the risk assessment level.

[0110] S603: Multiply the correction factor by the first stability score to generate the second stability score.

[0111] By analyzing the natural variation patterns of tower attitude, the attitude deviation trend in the future period is predicted, and an adjustment mechanism is designed in which the correction factor is negatively correlated with the predicted attitude deviation. This design can reasonably distinguish between natural and abnormal changes when adjusting the score. When the predicted natural deviation is large, the risk assessment level is appropriately reduced, and when the predicted natural deviation is small, the risk assessment level is increased, thereby avoiding false alarms caused by natural changes. By multiplying the correction factor with the initial stability score to obtain the corrected score, dynamic optimization of tower stability assessment is achieved, improving the accuracy and reliability of the assessment results.

[0112] S604: Substitute the correlation influence coefficient into the fourth preset formula to calculate the correlation adjustment factor.

[0113] The fourth preset formula is: ,

[0114] in: For correlation adjustment factors, R is the correlation sensitivity coefficient, and R is the correlation influence coefficient.

[0115] The reason for using a subtraction form in the fourth preset formula is that when the correlation effect is negative, the correlation adjustment factor should be less than 1 to reduce the stability score; when the correlation effect is small, the correlation adjustment factor is close to 1 to maintain the original score level. The formula design considers a linear structure to facilitate engineering applications and parameter adjustment. The settings can control the strength of the correlation effect and ensure that the calculation results are within a reasonable range, avoiding over-amplification or under-amplification of the correlation effect.

[0116] S605: Multiply the correlation adjustment factor by the second stability score to generate the third stability score.

[0117] The calculated correlation adjustment factor is arithmetically multiplied with the second stability score to obtain the third stability score. This multiplication operation can maintain the continuity of the score and reasonably reflect the moderating effect of correlation on stability. The third stability score integrates factors from three levels: the state of the tower itself, the natural change trend, and the influence of the correlated tower.

[0118] S606: Adjust the third stability score based on the first environmental impact coefficient to generate the target stability score.

[0119] Based on the first environmental impact coefficient calculated in the aforementioned steps, the third stability score is further adjusted to generate the final target stability score. This adjustment process uses a similar multiplication operation method to ensure that the environmental impact is appropriately reflected in the final score. The environmental impact coefficient reflects the comprehensive impact of environmental factors such as geological conditions and soil moisture on the stability of the tower.

[0120] By introducing a correlation sensitivity coefficient to calculate a correlation adjustment factor and adopting a step-by-step adjustment approach, the stability score is first corrected using the correlation adjustment factor, and then further adjusted based on the environmental impact coefficient. This adjustment mechanism allows correlation and environmental impact to have a reasonable regulatory effect on the score, avoiding mutual interference from multiple influencing factors. By setting the correlation sensitivity coefficient, the intensity of the correlation effect can be flexibly controlled, making the score adjustment more accurate. This multi-level score adjustment method can comprehensively reflect the effect of various influencing factors on tower stability, improving the accuracy and reliability of the final assessment results.

[0121] Specifically, based on the first environmental impact coefficient, the third stability score is adjusted to generate the target stability score, including:

[0122] S6061: Substitute the first environmental impact coefficient into the fifth preset formula to calculate the environmental adjustment factor.

[0123] The fifth preset formula is: ,

[0124] in: As an environmental adjustment factor, E is the environmental sensitivity coefficient (usually taken as 0.15), and E is the first environmental impact coefficient.

[0125] The reason for using a subtraction form in the fifth preset formula is that when environmental conditions deteriorate (E value increases), the environmental adjustment factor should be reduced accordingly to lower the stability score; when environmental conditions are good (E value is small), the environmental adjustment factor is close to 1 to maintain the score level. This design is not only in line with engineering practice experience, but also facilitates parameter adjustment and system maintenance.

[0126] S6062: Multiply the environmental adjustment factor by the third stability score to generate the target stability score.

[0127] By introducing an environmental sensitivity coefficient to calculate an environmental adjustment factor, a quantitative relationship between environmental impact and stability score is established. This design allows changes in environmental conditions to reasonably regulate the score through the environmental adjustment factor. When environmental conditions deteriorate, the score is appropriately reduced, while when environmental conditions are favorable, the score level is maintained. By setting the environmental sensitivity coefficient, the intensity of environmental impact can be precisely controlled, avoiding excessive amplification or weakening of environmental impact. Multiplying the environmental adjustment factor by the score yields the final target stability score, achieving refined quantification of environmental impact and improving the accuracy of tower stability assessment.

[0128] In this embodiment, an initial stability score is generated by acquiring the attitude information of the target tower, and an environmental impact coefficient is generated by combining geographical features and environmental information. At the same time, the influencing factors of related towers are considered, and the natural change patterns are analyzed based on historical attitude change data. Finally, the target stability score is obtained through multi-level scoring adjustments. This comprehensive evaluation method not only considers the state of the tower itself, but also includes multiple dimensions of influencing factors such as environmental conditions, related influences, and natural changes. It can more accurately reflect the actual stability state of the tower. By triggering an early warning mechanism through a preset scoring threshold, potential risks can be detected in a timely manner, providing reliable decision-making basis for operation and maintenance personnel, effectively reducing the probability of false alarms and missed alarms, and accurately assessing the actual stability state of the tower.

[0129] Example 2:

[0130] This embodiment provides a power pole tower settlement attitude monitoring system, including:

[0131] The first acquisition module is used to acquire the first attitude information of the target tower at the current moment, and generate the first stability score of the target tower based on the first attitude information.

[0132] The second acquisition module is used to acquire the first geographical features of the target tower's location and the first environmental information of the target tower within a first preset time period after the current time. Combining the first geographical features and the first environmental information, it generates the first environmental impact coefficient of the target tower within the first preset time period.

[0133] The third acquisition module is used to acquire the second geographical features of the location of the associated towers associated with the target tower, and the second environmental information of the associated towers within a first preset time period. Combining the second geographical features and the second environmental information, the module generates the second environmental impact coefficient of the associated towers within the first preset time period.

[0134] The module is used to combine the second environmental impact coefficient and the second attitude information of the associated tower to generate the associated impact coefficient of the target tower;

[0135] The fourth acquisition module is used to acquire the attitude change data of the target tower within a second preset time period before the current moment, and generate the natural attitude change amount of the target tower within a first preset time period based on the attitude change data.

[0136] The adjustment module is used to adjust the first stability score based on the natural change in attitude, generate the second stability score of the target tower, and adjust the second stability score in combination with the correlation influence coefficient and the first environmental influence coefficient to generate the target stability score. When the target stability score is lower than the preset score, an early warning message is generated.

[0137] Example 3:

[0138] This embodiment provides an electronic device, including a processor 1, a memory 5, a user interface 3, and a network interface 4. The memory 5 is used to store instructions, the user interface 3 and the network interface 4 are used to communicate with other devices, and the processor 1 is used to execute the instructions stored in the memory 5 so that the electronic device performs the method in embodiment 1. The processor 1, the memory 5, the user interface 3 and the network interface 4 are connected and communicate with each other through a communication bus 2.

[0139] User interface 3 can be a display screen or a standard wired or wireless interface.

[0140] Network interface 4 can be a standard wired interface or a wireless interface (such as a WI-FI interface).

[0141] The processor 1 includes one or more processing cores. The processor 1 connects to various parts of the entire electronic device (such as a server) using various interfaces and lines. It executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 5, and calling data stored in the memory 5.

[0142] The memory 5 includes a Random Access Memory (RAM), and may also include a Read-Only Memory. Optionally, the memory 5 includes a non-transitory computer-readable storage medium. The memory 5 is used to store instructions, programs, codes, code sets or instruction sets. The memory 5 may include a storage program area and a storage data area. Among them, the storage program area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing Example 1, etc.

[0143] Example 4:

[0144] This embodiment provides a computer-readable storage medium, and the medium stores a computer program that can be loaded and executed by the processor 1 to implement the method in Example 1.

[0145] Among them, the computer-readable storage medium may include, but is not limited to: USB flash drives, Read-Only Memories (ROMs), Random Access Memories (RAMs), mobile hard disks, magnetic disks or optical discs, etc., various media that can store computer programs.

[0146] Example 5:

[0147] In this embodiment, taking the tension tower numbered T328 as an example, its settlement attitude is monitored as follows:

[0148] The system obtains the first attitude information of the T328 tower pole. The inclination angle in the X-axis direction measured by the JY901S gyroscope sensor installed at the top of the tower pole is 2.3°, and the inclination angle in the Y-axis direction is 1.8°. The comprehensive inclination angle is calculated to be 2.9° through vector synthesis. At the same time, the BMP280 barometric altimeter measures the current altitude to be 587.23 m. Compared with the initial altitude of 587.45 m recorded during installation, the settlement depth is calculated to be 220 mm.

[0149] For the 220 kV tension tower, the system预设的角度 - 分值映射函数 Adopts a piecewise function: when the inclination angle x ≤ 2°, ; when 2° < x ≤ 5°, ; when x > 5°, , substituting the measured inclination angle of 2.9° into the function, the inclination score points.

[0150] Settlement - score mapping function Also use a piecewise function: when the settlement depth \(x\leq100\mathrm{mm}\), ; when \(100\mathrm{mm}<x\leq300\mathrm{mm}\), ; when \(x > 300\mathrm{mm}\), , substitute the measured settlement depth of \(220\mathrm{mm}\) into the function to obtain the settlement score points.

[0151] Considering that T328 is a strain tower, its requirement for tilt stability is higher than that for settlement stability. The system sets the tilt weight , the settlement weight , substitute the score and weight into the calculation formula: points.

[0152] This score indicates that the current stability status of the T328 tower is at a lower-middle level. Combining historical data analysis, although this situation has not reached the level of immediate danger, it already requires key attention. Especially in the upcoming rainy season, further evaluation needs to be carried out in combination with environmental factors and the influence of associated towers.

[0153] Further, if the tower numbered T328 is located in a sandy soil area (geological influence coefficient 0.8), the slope measurement value is \(15^{\circ}\), and it is predicted that the average soil humidity will reach \(65\%\) within the next 72 hours, substitute into the relevant formula for calculation:

[0154] Slope influence coefficient ;

[0155] Soil humidity influence coefficient ;

[0156] Finally, the first environmental influence coefficient \(= 0.8\times0.4 + 1.2\times0.3+0.75\times0.3 = 0.905\).

[0157] Further, the associated towers of the strain tower numbered T328 include the upstream T327 straight tower and the downstream T329 straight tower. For these associated towers, the system uses the same method as the target tower to obtain and evaluate their geographical features and environmental information, which can ensure the consistency of the evaluation criteria. The second geographical feature of the location of the T327 tower shows that the geological type is weathered rock (geological influence coefficient 0.85), and the slope is \(12^{\circ}\); the geographical features of the T329 tower are: the geological type is sandy soil (geological influence coefficient 0.8), and the slope is \(18^{\circ}\).

[0158] Considering the complexity of mountainous terrain, the associated towers may be located in different microclimates than the target tower. For example, tower T327 is located on a ridge, while tower T329 is located on the side of a valley. Even if they are not far apart, their local meteorological conditions may be significantly different. Therefore, the system collects second environmental information for the associated towers, including meteorological forecast data for the next 72 hours (consistent with the first preset duration) and soil moisture monitoring data.

[0159] For Tower T327:

[0160] Slope Influence Coefficient ;

[0161] The predicted soil moisture content is 55%, and the soil moisture influence coefficient is... ;

[0162] The second environmental impact coefficient of T327 tower = 0.85×0.4 + 1.14×0.3 + 0.85×0.3 = 0.934.

[0163] For Tower T329:

[0164] Slope Influence Coefficient ;

[0165] The predicted soil moisture content is 70%, and the soil moisture influence coefficient is... ;

[0166] The second environmental impact coefficient of tower T329 is 0.8×0.4+1.26×0.3+0.70×0.3=0.898.

[0167] Furthermore, the influence of the upstream and downstream related towers T327 and T329 of the tension tower numbered T328 needs to be calculated separately and then integrated. First, the distance information between the related towers and the target tower is obtained: the distance from T327 to T328 is 380m, and the distance from T329 to T328 is 420m. The distance influence coefficient reference table preset by the system is established based on a large amount of measured data, and the distance is divided into multiple intervals: 0.9 for within 300m, 0.7 for 300-500m, 0.5 for 500-800m, and 0.3 for above 800m. Based on this, the distance attenuation coefficients of T327 and T329 are determined to be 0.7 and 0.7, respectively.

[0168] The second attitude information of the associated towers was obtained through the same sensor system as the target tower. The overall tilt angle measured for tower T327 was 1.8° and the settlement depth was 150mm; the overall tilt angle measured for tower T329 was 2.5° and the settlement depth was 180mm. Using the same scoring standard as the target tower, the second stability score of tower T327 was calculated to be 78.5 points, and the second stability score of tower T329 was 65.2 points.

[0169] Substitute these data into the third preset formula Calculate the correlation influence coefficient.

[0170] For T327 tower: ;

[0171] For T329 tower: ;

[0172] Final correlation coefficient The weighted average is obtained as follows: .

[0173] Furthermore, the system sets a second preset duration of 30 days to collect historical attitude data within the preset duration. This data is collected hourly by sensors installed on the tower, including time series of tilt angle and settlement depth. The data shows that the tilt angle of the T328 tower gradually increased from 2.1° to 2.9° and the settlement depth increased from 180mm to 220mm during these 30 days. The system uses time series analysis methods, through data preprocessing, trend analysis and pattern recognition, to uncover the inherent laws of attitude changes.

[0174] First, the raw data is preprocessed, including outlier filtering and data smoothing. A moving average method is used to filter high-frequency noise, with a 24-hour window size to eliminate the influence of short-term factors such as daily temperature variations. Then, the least squares method is used to fit the trend of the processed data, yielding the variation functions of the tilt angle and settlement depth.

[0175] Tilting angle variation function: ;

[0176] Settlement depth variation function: ;

[0177] Where t is a time variable, and the unit is days.

[0178] The quadratic term in the function indicates that the change has an accelerating characteristic, which is consistent with the actual situation of the gradual softening of geological conditions.

[0179] Based on these functions, the system predicts the natural changes in attitude within the first preset time period (72 hours). By calculating the function value at t=3, it is found that the tilt angle is expected to increase by 0.085° and the settlement depth is expected to increase by 4.3 mm. These predicted values ​​constitute the basic parameters of the natural changes in attitude.

[0180] However, considering that natural changes are often influenced by multiple factors, the system also established a confidence interval analysis model. By calculating the standard deviation of historical data and setting a 95% confidence level, the possible range of the change was obtained:

[0181] Tilting angle change: 0.085±0.015°; Settlement depth change: 4.3±0.8mm.

[0182] Furthermore, the first stability score of the T328 tension tower was 52.68 points. Based on the natural changes in attitude, the first layer of adjustment was performed. Predictions showed that the tilt angle would increase by 0.085±0.015° and the settlement depth would increase by 4.3±0.8mm within the next 72 hours. The system converted these predicted values ​​into predicted attitude offsets, using a comprehensive displacement calculation formula: ,

[0183] in , These are weighting coefficients (with values ​​of 1.0 and 0.5 respectively). The change in angle. This represents the change in settlement.

[0184] The calculated predicted attitude offset is 0.092.

[0185] A correction factor is generated based on the predicted attitude offset, and the correction factor is negatively correlated with the offset: ,in The sensitivity coefficient (value 0.8) is used to calculate the correction factor, which is 0.926. Multiplying the first stability score by the correction factor yields the second stability score. point.

[0186] Considering the effects of the correlation impact coefficient (46.0) and the first environmental impact coefficient (0.905), the correlation adjustment factor is first calculated based on the correlation impact coefficient and then substituted into the fourth preset formula. The correlation adjustment factor was calculated. Multiply the second stability score by the association adjustment factor to obtain the third stability score: point.

[0187] Considering the environmental impact, the first environmental impact coefficient is substituted into the fifth preset formula. Calculate the environmental adjustment factor. The third stability score is multiplied by the environmental adjustment factor to obtain the final target stability score: point.

[0188] The system's preset warning threshold is 35 points. Therefore, the target stability score of tower T328 has fallen below the warning threshold. The system then generates a warning message, including: Warning level: Level 2 (yellow) warning; Reason for warning: The stability score is below the threshold, indicating a potential risk.

[0189] The main influencing factors are: decreased stability of associated towers (contribution rate 40%), worsening natural change trends (contribution rate 35%), and unfavorable environmental conditions (contribution rate 25%).

[0190] Recommended measures include: increasing the frequency of inspections, preparing emergency reinforcement plans, and closely monitoring the surrounding geological conditions.

[0191] The above examples illustrate the present invention only to aid in understanding it and are not intended to limit the scope of the invention. Those skilled in the art can make various simple deductions, modifications, or substitutions based on the ideas of this invention.

Claims

1. A method for monitoring the settlement attitude of power poles, characterized in that: The monitoring method includes: Obtain the first attitude information of the target tower at the current moment, and generate the first stability score of the target tower based on the first attitude information; The first geographical feature of the target tower's location and the first environmental information of the target tower within a first preset time period after the current time are obtained. The first environmental impact coefficient of the target tower within the first preset time period is generated by combining the first geographical feature and the first environmental information. Obtain the second geographical features of the location of the associated towers associated with the target tower, and the second environmental information of the associated towers within the first preset time period. Combine the second geographical features and the second environmental information to generate the second environmental impact coefficient of the associated towers within the first preset time period. By combining the second environmental impact coefficient and the second attitude information of the associated tower, the associated impact coefficient of the target tower is generated; Obtain the attitude change data of the target tower within a second preset time period before the current moment, and generate the natural attitude change amount of the target tower within the first preset time period based on the attitude change data; The first stability score is adjusted based on the natural attitude change amount to generate a second stability score for the target tower. The second stability score is then adjusted based on the correlation influence coefficient and the first environmental influence coefficient to generate a target stability score. When the target stability score is lower than a preset score, an early warning message is generated.

2. The method for monitoring the settlement attitude of power poles according to claim 1, characterized in that: The step of combining the first geographical feature and the first environmental information to generate the first environmental impact coefficient of the target tower within the first preset time period includes: Determine the geological influence coefficient corresponding to the geological type of the first geographical feature from the preset geological influence coefficient comparison table; Substitute the slope of the first geographical feature into the first preset formula to calculate the slope influence coefficient; Multiply the geological influence coefficient by the slope influence coefficient to generate the target geological influence coefficient; By combining the target geological influence coefficient and the first environmental information, a first environmental influence coefficient for the target tower within the first preset time period is generated.

3. The method for monitoring the settlement attitude of power poles according to claim 2, characterized in that: The step of combining the target geological influence coefficient and the first environmental information to generate the first environmental influence coefficient of the target tower within the first preset time period includes: Based on the first environmental information, determine the average soil moisture value of the target tower location within the first preset time period; Substitute the average soil moisture value into the second preset formula to calculate the soil moisture influence coefficient; The target geological influence coefficient and the soil moisture influence coefficient are weighted and summed to generate the first environmental influence coefficient of the target tower within the first preset time period.

4. The method for monitoring the settlement attitude of power poles according to claim 2, characterized in that: The step of generating the associated influence coefficient of the target tower by combining the second environmental influence coefficient and the second attitude information of the associated tower includes: Obtain the distance information between the associated tower and the target tower; Based on the distance information, the corresponding distance attenuation coefficient is determined from a preset distance influence coefficient lookup table; A second stability score for the associated tower is generated based on the second attitude information of the associated tower. Substituting the second stability score of the associated tower, the second environmental impact coefficient, and the distance attenuation coefficient into the third preset formula, the associated impact coefficient of the target tower is generated.

5. The method for monitoring the settlement attitude of power poles according to claim 1, characterized in that: The step of adjusting the first stability score based on the natural attitude change to generate a second stability score for the target tower includes: Based on the natural change in attitude, the predicted attitude offset of the target tower within the first preset time period is determined; A correction factor is generated based on the predicted attitude offset. The correction factor is multiplied by the first stability score to generate the second stability score.

6. The method for monitoring the settlement attitude of power poles according to claim 1, characterized in that: The step of adjusting the second stability score by combining the correlation impact coefficient and the first environmental impact coefficient to generate a target stability score includes: Substitute the correlation influence coefficient into the fourth preset formula to calculate the correlation adjustment factor; The correlation adjustment factor is multiplied by the second stability score to generate a third stability score; Based on the first environmental impact coefficient, the third stability score is adjusted to generate the target stability score.

7. The method for monitoring the settlement attitude of power poles according to claim 6, characterized in that: The step of adjusting the third stability score based on the first environmental impact coefficient to generate the target stability score includes: Substitute the first environmental impact coefficient into the fifth preset formula to calculate the environmental adjustment factor; The target stability score is generated by multiplying the environmental adjustment factor by the third stability score.

8. A power pole settlement attitude monitoring system, characterized in that, The monitoring system includes: The first acquisition module is used to acquire the first attitude information of the target tower at the current moment, and generate the first stability score of the target tower based on the first attitude information. The second acquisition module is used to acquire the first geographical features of the location of the target tower and the first environmental information of the target tower within a first preset time after the current time, and to generate the first environmental impact coefficient of the target tower within the first preset time by combining the first geographical features and the first environmental information. The third acquisition module is used to acquire the second geographical features of the location of the associated tower associated with the target tower, and the second environmental information of the associated tower within the first preset time period. Combining the second geographical features and the second environmental information, a second environmental impact coefficient of the associated tower within the first preset time period is generated. The module is used to combine the second environmental impact coefficient and the second attitude information of the associated tower to generate the associated impact coefficient of the target tower; The fourth acquisition module is used to acquire the attitude change data of the target tower within a second preset time period before the current moment, and generate the natural attitude change amount of the target tower within the first preset time period based on the attitude change data. The adjustment module is used to adjust the first stability score according to the natural change in attitude, generate a second stability score for the target tower, and adjust the second stability score in combination with the correlation influence coefficient and the first environmental influence coefficient to generate a target stability score. When the target stability score is lower than the preset score, an early warning message is generated.

9. An electronic device, characterized in that: The device includes a processor (1), a memory (5), a user interface (3), and a network interface (4). The memory (5) is used to store instructions. The user interface (3) and the network interface (4) are used to communicate with other devices. The processor (1) is used to execute the instructions stored in the memory (5) to cause the electronic device to perform the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The medium stores a computer program that can be loaded by the processor (1) and executed as described in any one of claims 1-7.

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