An artificial intelligence-based power transmission tower spiral anchor stability effect analysis method and system

Abstract

The application discloses a power transmission tower spiral anchor stability effect analysis method and system based on artificial intelligence, and the method comprises the following steps: acquiring stone block condition data, spiral anchor implantation condition data and environmental influence condition data of a spiral anchor implantation area of a power transmission tower; performing spiral anchor damage condition prediction analysis based on the stone block condition data and the spiral anchor implantation condition data of the spiral anchor implantation area of the power transmission tower, and obtaining a key marked spiral anchor; performing environmental influence analysis based on the environmental influence condition data of the key marked spiral anchor, and obtaining an environmental influence analysis result of the key marked spiral anchor; performing stability analysis based on the spiral anchor damage condition prediction analysis result and the environmental influence analysis result, and obtaining a stability analysis result of the key marked spiral anchor; and pushing the stability condition of the key marked spiral anchor according to the stability analysis result. The application realizes dynamic perception, accurate prediction and intelligent management and control of the stability of the spiral anchor of the power transmission tower.

Description

Technical Field

[0001] This invention relates to the field of data analysis technology, specifically to a method and system for analyzing the stability effect of transmission tower spiral anchors based on artificial intelligence. Background Technology

[0002] With the rapid expansion of ultra-high voltage power transmission networks, the stability of transmission towers in complex geological environments (such as mountainous areas, permafrost regions, and coastal saline soil areas) faces severe challenges. While helical anchors are widely used for tower foundation anchoring due to their ease of construction and strong pull-out bearing capacity, the following drawbacks still exist when using helical anchors:

[0003] Transmission towers are often built in complex terrains such as mountains and hills. The areas where helical anchors are installed often contain obstacles such as rocks and hard soil layers, which can easily cause structural damage to the anchor body during installation (such as blade deformation and rod bending), weakening its load-bearing capacity. Traditional methods rely on manual drilling and sampling to assess the risk of rocks around the helical anchor, which can only obtain local static data and cannot quantify the cumulative mechanical damage (such as scratching and stress concentration) caused by the surrounding rock clusters to the anchor rod. Furthermore, the dynamic coupling effect of soil chloride ion erosion and coating thickness in the helical anchor installation area is not included in the real-time assessment system, resulting in a large deviation in the prediction of helical anchor corrosion and deterioration, leading to uncontrollable hidden damage to the helical anchor. Existing helical anchor stability monitoring systems only collect the state of the anchor body itself, ignoring the seepage force amplification effect caused by groundwater level fluctuations and the synergistic damage of soil density degradation to the helical anchor body in the soil, resulting in a lag in the identification of helical anchor stability risks. Indiscriminate testing of all helical anchors leads to a waste of maintenance resources. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide an artificial intelligence-based method and system for analyzing the stability effect of helical anchors on transmission towers, which addresses the shortcomings of the prior art mentioned in the background. By accurately predicting the damage and stability of the helical anchors, the invention can issue early warnings before catastrophic accidents such as anchor failure leading to tower tilting or even collapse occur.

[0005] To solve the above technical problems, the present invention adopts the following technical solution:

[0006] An artificial intelligence-based method for analyzing the stability effect of transmission tower spiral anchors includes the following steps:

[0007] S1. Obtain data on the rock conditions in the area where the transmission tower's spiral anchor is implanted, data on the implantation of the spiral anchor, and data on the environmental impact of the spiral anchor.

[0008] S2. Based on the data on the rock conditions and the installation conditions of the helical anchors in the transmission tower installation area, predictive analysis of the damage to the helical anchors is performed to obtain the key marked helical anchors.

[0009] S3. Based on the environmental impact data of the key marked spiral anchors, conduct an environmental impact analysis to obtain the environmental impact analysis results of the key marked spiral anchors.

[0010] S4. Based on the predicted analysis results of damage to key marked spiral anchors and the analysis results of environmental impact, conduct stability analysis to obtain the stability analysis results of key marked spiral anchors; and push the stability status of key marked spiral anchors according to the stability analysis results of key marked spiral anchors.

[0011] Furthermore, in step S1, the data on the condition of stones in the area where the transmission tower spiral anchor is implanted includes data on the density, hardness, and sharpness of the stones in the implantation area.

[0012] Pit was drilled in the area where the helical anchor was to be implanted. The pit wall was scanned to identify the stones and obtain images of the pit wall. The images of the pit wall were processed to obtain the number of stones per unit volume and the stone outlines. The number of stones per unit volume was used as the stone density data. The roundness of the stones was obtained based on the stone outlines. The average roundness of the stones was used as the sharpness data of the stones. The hardness data of the stones was obtained using a point load tester.

[0013] The data on the installation of the helical anchor includes data on the installation depth of the helical anchor, data on the thickness of the helical anchor rod coating, and data on the chloride ion content in the soil of the installation area.

[0014] The installation depth data of the spiral anchor is obtained by using an inclination sensor and a depth encoder at the top of the spiral anchor drill rod; the thickness data of the spiral anchor rod coating is obtained by using a thickness gauge; and the chloride ion content data in the soil of the spiral anchor installation area is measured by taking points within a set radius centered on the area where the spiral anchor is to be installed.

[0015] Data on the environmental impact of the helical anchor includes data on the soil density where the helical anchor is located and data on groundwater level fluctuations.

[0016] Piezoresistive density sensors are pre-embedded around the helical anchor, and the soil density data at the location of the helical anchor is obtained through the data transmitted by the piezoresistive density sensors; groundwater level fluctuation data is obtained from the database.

[0017] Furthermore, in step S2, obtaining the key-marked spiral anchor includes the following steps:

[0018] S21. Based on the data of the helical anchor insertion depth, the density data, hardness data, and sharpness data of the stones in the insertion area, an impact analysis of the bearing capacity is conducted to obtain the results of the impact analysis of the helical anchor's bearing capacity.

[0019] S22. Based on the data on the thickness of the spiral anchor bolt coating and the data on the chloride ion content in the soil of the spiral anchor implantation area, the results of the analysis on the impact of the spiral anchor on durability are obtained.

[0020] S23. Based on the analysis results of the impact of the bearing capacity and durability of the helical anchor, the damage prediction analysis results of the helical anchor are obtained.

[0021] S24. Based on the damage prediction and analysis results of the helical anchors, the key marked helical anchors are obtained.

[0022] Furthermore, in step S21, the results of the influence analysis on the bearing capacity of the helical anchor include the following:

[0023] The attack intensity data of the stones in the helical anchor insertion area is obtained by dividing the hardness data of the stones by the reference hardness and then multiplying it by the sharpness data of the stones in the helical anchor insertion area. The damage degree of the helical anchor in the helical anchor insertion area is obtained by dividing the density data of the stones in the helical anchor insertion area by the standard density and then multiplying it by the attack intensity data of the stones in the helical anchor insertion area. The damage degree of the helical anchor in the helical anchor insertion area is then integrated over the helical anchor insertion depth data and divided by the helical anchor insertion depth data to obtain the impact analysis results of the helical anchor's bearing capacity.

[0024] Furthermore, in step S22, the results of the durability impact analysis of the helical anchor include the following:

[0025] The corrosion resistance of the helical anchor is quantified by dividing the anchor rod coating thickness data by the standard thickness. The damage to the helical anchor in the implantation area is quantified by dividing the difference between the chloride ion content data in the soil of the implantation area and the standard chloride ion content in the soil of the implantation area by the reference chloride ion difference. The corrosion resistance of the helical anchor and the damage to the helical anchor in the implantation area are multiplied by the standard values ​​of the corrosion resistance and damage of the helical anchor, respectively, to obtain the results of the impact analysis on the durability of the helical anchor.

[0026] Furthermore, in step S23, the results of the load-bearing capacity influence analysis and the durability influence analysis are weighted and summed to obtain the damage prediction analysis results of the helical anchor.

[0027] Furthermore, in step S24, if the damage prediction analysis result of the spiral anchor is greater than or equal to the set threshold for the damage prediction analysis result of the spiral anchor, then the corresponding spiral anchor is marked as a key spiral anchor.

[0028] Furthermore, in step S3, the data on the environmental impact of the key marked helical anchor includes the soil density data and groundwater level fluctuation data of the key marked helical anchor.

[0029] The soil density data of the key marked spiral anchor is divided by the standard soil density of the area where the spiral anchor is located to quantify the soil strength. The groundwater level fluctuation data of the key marked spiral anchor is integrated within the water level fluctuation period and then divided by the water level fluctuation period and the reference water level fluctuation data to quantify the seepage force intensity of the key marked spiral anchor. The environmental impact analysis results of the key marked spiral anchor are obtained by multiplying the soil strength of the key marked spiral anchor by the seepage force intensity.

[0030] Furthermore, in step S4, the predicted analysis results of the damage of the key marked spiral anchors are obtained from the predicted analysis results of the spiral anchor damage. The predicted analysis results and the environmental impact analysis results of the key marked spiral anchors are weighted and added together to obtain the stability analysis results of the key marked spiral anchors.

[0031] If the stability analysis result of the key marked spiral anchor is less than or equal to the set threshold for spiral anchor stability analysis results, the stability of the corresponding key marked spiral anchor is deemed qualified; if the stability analysis result of the key marked spiral anchor is greater than the set threshold for spiral anchor stability analysis results, the stability of the corresponding key marked spiral anchor is deemed unqualified.

[0032] Furthermore, this invention also proposes an artificial intelligence-based system for analyzing the stability effect of transmission tower spiral anchors, comprising:

[0033] The spiral anchor damage prediction and analysis module is used to predict and analyze the spiral anchor damage based on the rock condition data and spiral anchor installation data in the spiral anchor implantation area of ​​the transmission tower, and to identify the spiral anchors that are marked as key points.

[0034] The helical anchor environmental impact analysis module is used to perform environmental impact analysis based on the environmental impact data of key marked helical anchors, and obtain the environmental impact analysis results of key marked helical anchors.

[0035] The stability assessment and push module is used to perform stability analysis based on the damage prediction and analysis results and environmental impact analysis results of the key marked spiral anchors, and to obtain the stability analysis results of the key marked spiral anchors; and to push the stability status of the key marked spiral anchors based on the stability analysis results.

[0036] Compared with the prior art, the present invention, employing the above technical solution, has the following technical effects:

[0037] This invention acquires data on the rock conditions, anchor placement, and environmental impact of the helical anchors in the transmission tower anchor placement area; it predicts and analyzes the damage of each helical anchor based on the rock conditions and anchor placement data, and identifies key marked helical anchors based on the damage prediction analysis results; it then analyzes the environmental impact of each key marked helical anchor based on the environmental impact data; finally, it analyzes the stability of each key marked helical anchor based on the damage prediction analysis results and the environmental impact analysis results; and it pushes the stability status of each key marked helical anchor based on the stability analysis results. By integrating multi-source data such as geology, construction, and environment of the helical anchors, it establishes a [system / mechanism / database]. The closed-loop analysis system for helical anchor stability analysis enhances the safety of transmission tower helical anchors. By accurately predicting the damage and stability of helical anchors, it can issue early warnings before catastrophic accidents such as anchor failure leading to tower tilting or even collapse occur, providing valuable time for emergency repairs and reinforcement. Maintenance personnel no longer need to inspect all helical anchors with the same frequency and depth. The inspection cycle can be extended for anchors with high stability, while manpower and resources can be concentrated on key marked anchors for detailed inspection, reducing ineffective labor, avoiding resource waste caused by over-maintenance, and preventing risks caused by insufficient maintenance. This makes the allocation of resources such as spare parts and construction teams more rational and economical, breaking through the limitations of traditional monitoring methods and realizing dynamic perception, accurate prediction, and intelligent control of transmission tower helical anchor stability. Attached Figure Description

[0038] Figure 1 This is a flowchart illustrating the overall implementation of the present invention.

[0039] Figure 2 This is a flowchart illustrating the implementation process of obtaining the key marked spiral anchor of the present invention. Detailed Implementation

[0040] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and should not be used to limit the scope of protection of the present invention.

[0041] To achieve the above objectives, this invention proposes an artificial intelligence-based method for analyzing the stability effect of transmission tower spiral anchors, such as... Figure 1 As shown, the specific steps are as follows:

[0042] S1. Obtain data on the condition of rocks in the area where the transmission tower's helical anchor is installed, the installation status of the helical anchor, and the environmental impact on the helical anchor. Specifically:

[0043] Data on the stones in the area where the transmission tower's spiral anchor is implanted includes data on the density, hardness, and sharpness of the stones in the implanted area.

[0044] Pit was drilled within the area where the helical anchor was to be implanted. The pit walls were scanned, and the rocks were identified using processing software to obtain high-resolution images of the pit walls. These high-resolution images were then processed to obtain the number of rocks per unit volume and the outlines of the rocks. The number of rocks per unit volume was used as the density data of the rocks. The roundness of the rocks was obtained based on their outlines, and the average roundness of the rocks was used as the sharpness data of the rocks. The hardness data of the rocks was obtained using a point load testing instrument.

[0045] The data on the installation of the helical anchor includes data on the installation depth of the helical anchor, data on the thickness of the helical anchor rod coating, and data on the chloride ion content in the soil of the installation area.

[0046] The installation depth data of the helical anchor is obtained through the tilt sensor and depth encoder at the top of the helical anchor drill rod; the thickness data of the helical anchor rod coating is obtained through the thickness gauge; taking points (e.g., 3 points) within a radius of 0.5m centered on the area where the helical anchor is to be installed, a set of samples is taken at a depth of 1m (0 to 5m segment), the samples are processed, and the chloride ion content data in the soil of the helical anchor installation area is determined experimentally (e.g., silver nitrate titration or ion chromatography).

[0047] Data on the environmental impact of the helical anchor includes data on the soil density where the helical anchor is located and data on groundwater level fluctuations.

[0048] Piezoresistive density sensors are pre-embedded around the helical anchor, and the soil density data at the location of the helical anchor is obtained through the data transmitted by the piezoresistive density sensors; groundwater level fluctuation data is obtained from the database.

[0049] S2. Based on the data on the rock conditions and anchor installation status in the transmission tower's helical anchor implantation area, predictive analysis of helical anchor damage is performed to identify key marked helical anchors. For example... Figure 2 As shown, specifically:

[0050] S21. Based on the data of the helical anchor insertion depth, the density, hardness, and sharpness of the stones in the insertion area, a load-bearing capacity impact analysis is conducted to obtain the results of the helical anchor load-bearing capacity impact analysis. Specifically, this includes:

[0051] The attack intensity data of the stones in the helical anchor insertion area is obtained by dividing the hardness data of the stones by the reference hardness and then multiplying it by the sharpness data of the stones in the helical anchor insertion area. The damage degree of the helical anchor in the helical anchor insertion area is obtained by dividing the density data of the stones in the helical anchor insertion area by the standard density and then multiplying it by the attack intensity data of the stones in the helical anchor insertion area. The damage degree of the helical anchor in the helical anchor insertion area is then integrated over the helical anchor insertion depth data and divided by the helical anchor insertion depth data to obtain the impact analysis results of the helical anchor's bearing capacity.

[0052] It should be noted that the helical anchor relies on the interaction with the surrounding soil (such as friction, end bearing force, etc.) to provide bearing capacity; however, in strata containing a large number of rocks, the hardness, sharpness and density of the rocks can cause damage or destruction to the helical anchor body itself (such as scratching, indentation, bending or even breakage), thus significantly weakening its theoretical bearing capacity. The actual stone hardness is dimensionless, reflecting its hardness relative to a reference hardness; the higher the value, the harder the stone. The attack intensity is obtained by multiplying the actual stone's hardness relative to the reference hardness by the stone's sharpness. Sharp stones are more likely to scratch or pierce the anchor body than smooth stones, causing more severe localized damage to the auger anchor. Attack intensity quantifies the stone's potential to physically damage the anchor material by combining the stone's hardness and sharpness; the higher the attack intensity, the greater the potential damage to the auger anchor. The actual stone density is also dimensionless, reflecting the number of stones per unit volume; the higher the density, the denser the stones. Multiplying this by the stone attack intensity data, i.e., multiplying the stone's damage potential by the stone's number density in that area, yields the damage degree. The damage degree spatially combines the number of stones (i.e., density data) and the stone's destructive potential (i.e., attack intensity), quantifying the overall damage level that the auger anchor body may suffer in a specific area; the higher the value, the more severe the potential damage to the auger anchor body in that area. The damage level at each depth point is integrated along the entire implantation length (depth direction) of the helical anchor. This reflects the total damage load accumulated along the entire length of the anchor. The total damage load is then evenly distributed across the entire implantation depth, resulting in a depth-averaged damage index. This index represents the average damage level borne by the helical anchor along its entire anchoring length due to the characteristics of the rocks (i.e., hardness, sharpness, and density) in the implantation area. The larger this value is, the more severe the potential damage to the helical anchor caused by the rocky environment, and the greater the expected decrease in the helical anchor's bearing capacity relative to an ideal rock-free stratum. By analyzing the risk of mechanical damage to the anchor body caused by the characteristics of rocks in the helical anchor implantation area and quantifying the potential negative impact of this damage risk on the final bearing capacity of the helical anchor, the ambiguity of relying solely on experience or qualitative descriptions is avoided. Complex geological risks are transformed into a quantifiable and comparable indicator, improving the safety and reliability of helical anchor projects.

[0053] S22. Based on the data on the thickness of the helical anchor bolt coating and the chloride ion content in the soil of the helical anchor implantation area, the results of the impact analysis on the durability of the helical anchor were obtained. Specifically, this includes:

[0054] The corrosion resistance of the helical anchor is quantified by dividing the anchor rod coating thickness data by the standard thickness. The damage to the helical anchor in the implantation area is quantified by dividing the difference between the chloride ion content data in the soil of the implantation area and the standard chloride ion content in the soil of the implantation area by the reference chloride ion difference. The corrosion resistance of the helical anchor and the damage to the helical anchor in the implantation area are multiplied by the standard values ​​of the corrosion resistance and damage of the helical anchor, respectively, to obtain the results of the impact analysis on the durability of the helical anchor.

[0055] It is important to note that chloride ions, as strong electrolytes, significantly increase soil conductivity (i.e., reduce soil resistivity, a key indicator of soil conductivity that controls the magnitude of corrosion current; lower resistivity indicates a higher risk of corrosion) when present in excessively high concentrations. This promotes corrosion current flow (Faraday's law states that corrosion rate is directly proportional to current density), making helical anchors prone to pitting or crevice corrosion. Helical anchors (especially metal anchor bolts) are highly susceptible to corrosion in chloride-containing soils (such as coastal areas and saline soils), leading to anchor cross-sectional loss, reduced strength, and ultimately, failure. The anti-corrosion coating on the surface of the anchor bolt is the first line of defense against corrosion. Its thickness directly affects the protective effect and service life. By analyzing the two key factors of environmental corrosivity and protective capability of the helical anchor, the degree of threat to the durability of the helical anchor is obtained. The actual coating thickness of the helical anchor is dimensionless, reflecting the sufficiency of the coating relative to the standard thickness, which quantifies the anchor's own defensive capability. The actual chloride ion content is subtracted from the standard chloride ion content to calculate the excess amount of chloride ion concentration in the anchor's environment relative to the standard content. This excess amount is standardized, and the ratio reflects the degree to which the corrosivity of the environment exceeds the safety benchmark. The larger the ratio, the stronger the corrosiveness of the environment on the anchor bolt and the greater the potential for damage, which quantifies the attack of the external environment. The corrosion resistance and the degree of damage are first divided by their respective standard values ​​to standardize two indicators with different dimensions and ranges. The values ​​are standardized and compared on the same scale, and then multiplied to obtain a risk index that integrates the anchor's own protective capability and environmental corrosivity. The multiplicative relationship reflects that the risk is the result of the combined effect of insufficient protective capability and strong environmental corrosivity (e.g., even if the coating is thick and has strong corrosion resistance, the risk is still high if chloride ions are seriously exceeded; even if chloride ions are only slightly exceeded, the risk may still be significant if the coating is very thin and has weak corrosion resistance). The larger this value is, the higher the risk of the anchor failing due to corrosion in the current environment, and the shorter its expected service life. By analyzing the comprehensive impact of the chloride ion content of the soil in the environment where the anchor is located and the thickness of its own coating on its service life and structural integrity, the safety and reliability of the anchor structure throughout its entire life cycle can be ensured, and premature failure due to corrosion can be avoided.

[0056] S23. The results of the load-bearing capacity influence analysis and the durability influence analysis of the helical anchor are weighted and added together to obtain the damage prediction analysis results of the helical anchor.

[0057] It is important to note that the results of the previously conducted separate analyses of the impact on bearing capacity and durability are integrated to obtain a comprehensive quantitative index for predicting the overall failure risk of the helical anchor. Helical anchor failure can stem from two main mechanisms: first, short-term sudden failure, caused by adverse geological conditions in the implantation area (such as rocks), leading to mechanical damage, deformation, or fracture of the anchor body under stress (corresponding to the results of the bearing capacity impact analysis); second, long-term gradual failure, caused by environmental corrosion (chloride ions), leading to gradual deterioration, thinning, and strength reduction of the anchor material, ultimately rendering it unable to withstand loads during its service life (corresponding to the results of the durability impact analysis). Integrating these two distinct but crucial risk sources forms a comprehensive failure prediction analysis result, used to predict the overall risk level of a particular helical anchor's future failure (whether short-term or long-term). By comparing the relative risk levels of different helical anchors, the helical anchors with the highest risk in the entire project, requiring the most attention or priority for intervention, are identified. The two standardized risk indicators (i.e., the results of the bearing capacity impact analysis: quantifying the potential weakening of the anchor's mechanical strength by geological rocks) are combined to form a comprehensive risk prediction analysis. The degree of risk is determined by the weighted summation of two risk indicators (higher values ​​indicate higher risk). The two risk indicators may not contribute equally to the final failure. The weighted risk values ​​are then superimposed (a helical anchor may face both risks simultaneously, and its overall failure risk is the sum of their contributions). The final output is a damage prediction analysis result, a comprehensive quantitative indicator representing the overall probability or risk level of any form of failure (structural failure or corrosion failure) of the helical anchor in the future. This provides a unified and comparable benchmark for assessing the overall safety of the helical anchor, transcending the limitations of a single risk type. By weighting and summing the quantitative results of bearing capacity risk (geological damage) and durability risk (environmental corrosion), a comprehensive damage prediction analysis result is generated, comprehensively quantifying the overall failure risk of the helical anchor (covering short-term mechanical damage and long-term corrosion damage). This enables horizontal comparison and prioritization of risks among different helical anchors, ensuring the long-term safe and stable operation of the helical anchor engineering structure.

[0058] S24. If the damage prediction analysis result of the spiral anchor is greater than or equal to the set threshold for the damage prediction analysis result of the spiral anchor, then the corresponding spiral anchor is marked as a key spiral anchor.

[0059] It should be noted that by comparing the predicted damage analysis results of each helical anchor with the set threshold for predicted damage analysis results of the helical anchor, the comparison between the risk and safety boundary corresponding to each helical anchor is quantified, the acceptable risk and unacceptable risk of each helical anchor are defined, and helical anchors with unacceptable risks are marked, thereby focusing the risk and ensuring the safety and reliability of the structure throughout its entire life cycle at the lowest cost, and avoiding chain disasters caused by the failure of local anchor points.

[0060] S3. Based on the environmental impact data of the key marked helical anchors, an environmental impact analysis was conducted to obtain the results of the environmental impact analysis of the key marked helical anchors. Specifically:

[0061] The data on the environmental impact of the key marked helical anchors include soil density data and groundwater level fluctuation data.

[0062] The soil density data of the key marked spiral anchor is divided by the standard soil density of the area where the spiral anchor is located to quantify the soil strength. The groundwater level fluctuation data of the key marked spiral anchor is integrated within the water level fluctuation period and then divided by the water level fluctuation period and the reference water level fluctuation data to quantify the seepage force intensity of the key marked spiral anchor. The environmental impact analysis results of the key marked spiral anchor are obtained by multiplying the soil strength of the key marked spiral anchor by the seepage force intensity.

[0063] It should be noted that the environmental impact analysis of each key marked helical anchor, based on soil density data and groundwater level fluctuation data, is a process of in-depth environmental sensitivity analysis of the identified high-risk helical anchors (i.e., key marked helical anchors). Its core function is to quantify the cumulative impact of dynamic changes in the external environment on the stability of high-risk helical anchors. For the high-risk helical anchors identified in the early stage, the analysis further examines the two key environmental factors of soil density and groundwater level fluctuation at their locations, analyzing how these dynamic changes exacerbate the failure risk of the helical anchor points. The soil density is divided by the standard soil density to identify and quantify the weakness of the supporting capacity of the soil around the anchor point. The groundwater level fluctuation is integrated within the fluctuation period and then divided by the fluctuation period and the reference water level fluctuation to obtain the average water level fluctuation intensity within the period. The integrated value reflects the cumulative hydraulic impact of water level fluctuation on the anchor body. Dividing the integrated value by the fluctuation period can eliminate the influence of the time dimension and reveal the degree of harm of hydraulic cyclic load on the anchor body.

[0064] S4. Based on the predicted analysis results of damage to key marked spiral anchors and the environmental impact analysis results, a stability analysis is conducted to obtain the stability analysis results of the key marked spiral anchors; the stability status of the key marked spiral anchors is then disseminated based on the stability analysis results. Specifically:

[0065] The damage prediction analysis results of the key marked spiral anchors are obtained from the damage prediction analysis results of the spiral anchors. The weighted analysis results of the prediction analysis results and the environmental impact analysis results of the key marked spiral anchors are added together to obtain the stability analysis results of the key marked spiral anchors.

[0066] It should be noted that, based on the previously identified risks of the anchor point itself (i.e., geological damage and corrosion deterioration) and the risks of the dynamic environment in which the anchor point is located (i.e., soil strength + seepage force), the risks of self-damage and environmental disturbance are coupled, and dynamic weights are set to reflect the relative importance of the two-path risks of self-damage and environmental disturbance. By comprehensively considering the risks of anchor point self-damage and environmental disturbance, a quantitative basis for stability decision-making is obtained, providing a solid foundation for the safety management of helical anchors.

[0067] If the stability analysis result of the key marked helical anchor is less than or equal to the set threshold for the stability analysis result of the helical anchor, the stability of the corresponding key marked helical anchor is deemed qualified; if the stability analysis result of the key marked helical anchor is greater than the set threshold for the stability analysis result of the helical anchor, the stability of the corresponding key marked helical anchor is deemed unqualified. The stability status of each key marked helical anchor is pushed out in this way.

[0068] It should be noted that the stability of the helical anchor is determined by the threshold of the stability analysis results, and risk information is pushed in a targeted manner. This provides a clear safety boundary for complex risks, avoids ambiguous decision-making, ensures that risk information reaches the execution end directly, forms a management closed loop, and thus safeguards the bottom line of the safety of critical infrastructure. Redundant resources are released for qualified helical anchor points, improving resource utilization.

[0069] Example:

[0070] 1. Raw data collection

[0071] The data on the rock conditions in the spiral anchor implantation area are shown in Table 1.

[0072] Table 1. Data on the condition of rocks in the area where the spiral anchor was installed.

[0073]

[0074] The data on the installation of the spiral anchor are shown in Table 2.

[0075] Table 2. Data on the installation of spiral anchors

[0076]

[0077] The environmental impact data of the spiral anchor are shown in Table 3.

[0078] Table 3. Data on the environmental impact of the spiral anchor.

[0079]

[0080] 2. The results of the damage prediction analysis are shown in Table 4.

[0081] Table 4. Results of Damage Prediction Analysis

[0082]

[0083] 3. Key markings for determining the spiral anchor.

[0084] The key marking criteria are: damage probability > 30% or damage level ≥ moderate.

[0085] The key marked spiral anchors are: A-02, A-04, and A-05.

[0086] 4. The results of the environmental impact analysis of the key marked spiral anchors are shown in Table 5.

[0087] Table 5. Environmental Impact Analysis Results of Key Marked Spiral Anchors

[0088]

[0089] 5. The results of the stability analysis of the key marked spiral anchors are shown in Table 6.

[0090] Table 6. Results of stability analysis of key marked spiral anchors

[0091]

[0092] 6. Example of highlighting the stability status of the spiral anchor.

[0093] [Early Warning Notice Regarding the Stability of the Spiral Anchor on Transmission Tower xxx]

[0094] Test date: 2024-06-01.

[0095] Location: Transmission tower xxx.

[0096] Emergency Warning:

[0097] Spiral Anchor A-04: Stability Index 0.42 (extremely unstable);

[0098] Risk factors: Severe geological fissures + highly corrosive environment + poor implantation quality;

[0099] Recommendation: Arrange for immediate inspection and reinforcement.

[0100] Key areas of focus:

[0101] Spiral Anchor A-02: Stability Index 0.58 (Unstable);

[0102] Risk factors: Moderate geological conditions + strong environmental corrosion;

[0103] Recommendation: Strengthen monitoring and arrange inspections within two weeks.

[0104] Normal monitoring:

[0105] Spiral Anchor A-05: Stability Index 0.76 (Basically Stable);

[0106] Recommendation: Monitor monthly as usual.

[0107] Good condition:

[0108] Spiral anchors A-01 and A-03: good stability, continue routine monitoring;

[0109] Next test date: 2024-07-01.

[0110] This invention also proposes an artificial intelligence-based system for analyzing the stability of transmission tower helical anchors, including a helical anchor damage prediction and analysis module, a helical anchor environmental impact analysis module, a stability judgment and push module, and a computer program that can run on a processor. It should be noted that each module in the above system corresponds to a specific step of the method provided in this invention, possessing the corresponding functional modules and beneficial effects for executing the method. Technical details not described in detail in this embodiment can be found in the method provided in this invention.

[0111] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. An artificial intelligence-based power transmission tower spiral anchor stability effect analysis method, characterized in that, The method comprises the following steps: S1, obtaining stone block condition data, spiral anchor implantation condition data and environmental influence data of a spiral anchor implantation area of a power transmission tower, the stone block condition data of the spiral anchor implantation area of the power transmission tower comprising density data, hardness data and sharpness data of stone blocks in the implantation area; the spiral anchor implantation condition data comprising spiral anchor implantation depth data, spiral anchor rod coating thickness data and chlorine ion content data in soil of the spiral anchor implantation area; the environmental influence data of the spiral anchor comprising soil density data and underground water level fluctuation data of the spiral anchor; S2, performing spiral anchor damage condition prediction analysis based on the stone block condition data and the spiral anchor implantation condition data of the spiral anchor implantation area of the power transmission tower, and obtaining a key marked spiral anchor, wherein the key marked spiral anchor is obtained by the following steps: S21, performing bearing capacity influence analysis on the spiral anchor according to the spiral anchor implantation depth data, the density data, the hardness data and the sharpness data of the stone blocks in the implantation area, and obtaining bearing capacity influence analysis results of the spiral anchor, wherein the bearing capacity influence analysis results of the spiral anchor are obtained by the following steps: dividing the hardness data of the stone blocks in the spiral anchor implantation area by a reference hardness and multiplying the sharpness data of the stone blocks in the spiral anchor implantation area to obtain attack intensity data of the stone blocks in the spiral anchor implantation area; dividing the density data of the stone blocks in the spiral anchor implantation area by a standard density and multiplying the attack intensity data of the stone blocks in the spiral anchor implantation area to obtain spiral anchor damage degree in the spiral anchor implantation area; integrating the spiral anchor damage degree in the spiral anchor implantation area on the spiral anchor implantation depth data and dividing the spiral anchor implantation depth data to obtain the bearing capacity influence analysis results of the spiral anchor; S22, obtaining durability influence analysis results of the spiral anchor according to the spiral anchor rod coating thickness data and the chlorine ion content data in the soil of the spiral anchor implantation area, wherein the durability influence analysis results of the spiral anchor are obtained by the following steps: dividing the rod coating thickness data of the spiral anchor by a standard thickness to quantify the corrosion resistance of the spiral anchor; dividing the difference between the chlorine ion content data in the soil of the spiral anchor implantation area and the standard chlorine ion content in the soil of the implantation area by a reference chlorine ion difference to quantify the damage degree of the spiral anchor implantation area to the spiral anchor; multiplying the corrosion resistance of the spiral anchor and the damage degree of the spiral anchor implantation area to the spiral anchor by a corrosion resistance standard value and a damage degree standard value respectively to obtain the durability influence analysis results of the spiral anchor; S23, obtaining spiral anchor damage condition prediction analysis results according to the bearing capacity influence analysis results and the durability influence analysis results of the spiral anchor; S24, obtaining the key marked spiral anchor according to the spiral anchor damage condition prediction analysis results; S3, performing environmental influence analysis based on the environmental influence data of the key marked spiral anchor, and obtaining key marked spiral anchor environmental influence analysis results, wherein the environmental influence data of the key marked spiral anchor comprises soil density data and underground water level fluctuation data of the key marked spiral anchor. The soil density data where the key marked screw anchor is located is divided by the standard soil density of the area where the key marked screw anchor is located to quantify the soil strength where the key marked screw anchor is located; the groundwater level fluctuation data where the key marked screw anchor is located is integrated in the water level fluctuation period and then divided by the water level fluctuation period and the reference groundwater level fluctuation data to quantify the seepage force acting strength of the key marked screw anchor; the soil strength where the key marked screw anchor is located is multiplied by the seepage force acting strength to obtain the environmental impact analysis result of the key marked screw anchor; S4, based on the damage situation prediction analysis result and the environmental impact analysis result of the key marked screw anchor, stability analysis is performed to obtain the stability analysis result of the key marked screw anchor; the stability situation of the key marked screw anchor is pushed according to the stability analysis result of the key marked screw anchor. 2.The method of claim 1, wherein, In step S1, a pit is explored in the area where the screw anchor needs to be implanted, the pit wall is scanned, stones are identified, a pit wall picture is obtained, the pit wall picture is processed, the number of stones per unit volume and the stone profile are obtained, the number of stones per unit volume is taken as the density data of the stones, and the stone roundness is obtained according to the stone profile, and the average value of the stone roundness is taken as the sharpness data of the stones; the hardness data of the stones is obtained by using a point load tester; The implantation depth data of the screw anchor is obtained through the inclination sensor and the depth encoder at the top of the screw anchor drill rod; the screw anchor rod coating thickness data is obtained by using a thickness gauge; the soil chloride content data in the screw anchor implantation area is measured by taking points within a set radius centering on the area where the screw anchor needs to be implanted. The piezoresistive density sensor is pre-buried around the screw anchor, and the soil density data where the screw anchor is located is obtained through the data transmitted by the piezoresistive density sensor; the groundwater level fluctuation data is obtained from the database. 3.The method of claim 1, wherein, In step S23, the bearing capacity influence analysis result and the durability influence analysis result of the screw anchor are weighted and added to obtain the damage situation prediction analysis result of the screw anchor. 4.The method of claim 3, wherein, In step S24, if the damage situation prediction analysis result of the screw anchor is greater than or equal to the set screw anchor damage situation prediction analysis result threshold, the corresponding screw anchor is a key marked screw anchor. 5.The method for analyzing the stability effect of a spiral anchor of a power transmission tower based on artificial intelligence according to claim 1, wherein In step S4, the key marked screw anchor damage situation prediction analysis result is obtained from the screw anchor damage situation prediction analysis result, and the prediction analysis result and the key marked screw anchor environmental impact analysis result are weighted and added to obtain the key marked screw anchor stability analysis result; If the key marked screw anchor stability analysis result is less than or equal to the set screw anchor stability analysis result threshold, it is determined that the stability situation of the corresponding key marked screw anchor is qualified; if the key marked screw anchor stability analysis result is greater than the set screw anchor stability analysis result threshold, it is determined that the stability situation of the corresponding key marked screw anchor is unqualified.

6. The system for applying the method for analyzing the stability effect of the spiral anchor of the power transmission tower based on artificial intelligence according to any one of claims 1-5, characterized in that, Comprise: The screw anchor damage situation prediction analysis module is used for performing screw anchor damage situation prediction analysis based on the stone condition data and the screw anchor implantation condition data of the power transmission tower screw anchor implantation area to obtain a key marked screw anchor; The spiral anchor environmental impact analysis module is configured to perform environmental impact analysis based on the environmental impact data of the key marked spiral anchor, and obtain a key marked spiral anchor environmental impact analysis result. The stability condition judgment and pushing module is configured to perform stability analysis based on the damage prediction analysis result and the environmental impact analysis result of the key marked spiral anchor, and obtain a key marked spiral anchor stability analysis result. The key marked spiral anchor stability condition is pushed according to the key marked spiral anchor stability analysis result.

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