Building electrical safety risk analysis and evaluation method based on big data

Abstract

The invention provides a building electrical safety risk analysis and evaluation method based on big data, and the method comprises the steps: obtaining the burial depth information of different pipelines, calculating the axial offset and bending radius change of the pipelines in combination with the characteristics of a continuous settlement distribution field and a settlement region of a foundation, determining the geometric shape change of a pre-buried cable pipeline, and generating a pipeline deformation curved surface; determining a connection mode based on the geometrical shape of the pipeline, carrying out gradient analysis and curvature calculation on the deformation curved surface of the pipeline, extracting local bending deformation and a stress concentration area, and determining the internal stress distribution of the cable in combination with the connection mode and the environment temperature; and determining a crack risk assessment result according to the fatigue crack initiation probability of the sheath, and determining the material of the to-be-replaced pipeline and the structural deformation corresponding to the geometrical shape according to the crack risk assessment result and the service life of the pipeline.

Description

Technical Field

[0001] This invention relates to the field of information technology, and in particular to a method for analyzing and assessing building electrical safety risks based on big data. Background Technology

[0002] Uneven ground settlement is crucial for the safe operation of electrical pipelines, directly impacting the stability of urban infrastructure and public safety. Ground settlement can cause cable path deformation, stress concentration, and fatigue failure of insulation materials, leading to electrical faults or even major accidents. With rapid urbanization, differential ground settlement in densely built-up areas is becoming increasingly prominent, making its impact on the long-term performance of electrical pipelines a key issue for ensuring power grid reliability. Current research largely relies on static analysis or single-condition assumptions, neglecting the dynamic evolution of ground settlement and the long-term response of cables under complex stress environments. This approach struggles to capture the non-uniformity of settlement areas and the accumulation of microscopic damage to cable materials under alternating stress, resulting in significant discrepancies between predicted and actual outcomes. Geometric deformation of cable paths caused by differential ground settlement is one of the core challenges. When the settlement rates differ across different areas of the foundation, embedded cable ducts may bend or experience localized compression, creating complex paths outside of the design specifications. For example, a section of cable duct may bend due to ground settlement on one side, causing continuous friction between the duct's inner wall and the cable's outer sheath, resulting in sheath surface wear or crack initiation. This geometric deformation further leads to uneven stress distribution within the cable, especially under alternating tension and compression, accelerating fatigue crack propagation in the sheath material and increasing the risk of insulation failure. Another key challenge is that existing analytical methods struggle to adjust structural deformation in real time based on dynamic settlement monitoring data. Furthermore, the continuous deformation characteristics of the cable path require comprehensive analysis of the coupling relationship between multi-point settlement and the mechanical response of the pipeline material. The lack of a dynamic adjustment mechanism in current technology results in inaccurate fault prediction time windows, affecting the timeliness and effectiveness of maintenance strategies. For example, a cable segment that fails to identify local stress concentrations in a timely manner may develop from a minor crack into a serious insulation fault within a short period. Therefore, how to dynamically monitor foundation settlement data, adjust the influence coefficients of cable path geometric deformation and stress distribution in real time, and accurately predict insulation fault time windows has become a crucial issue in optimizing electrical pipeline maintenance strategies. Summary of the Invention

[0003] This invention provides a method for analyzing and assessing building electrical safety risks based on big data, mainly including: The height of the foundation from the preset horizontal plane is obtained, the settlement rate is statistically analyzed, and the characteristics of the settlement area are determined by combining the characteristics of the foundation soil layer, geological conditions and construction history. Based on the settlement rate and the characteristics of the settlement area, a continuous settlement distribution is generated, the soil layer compression modulus is determined, and a continuous settlement distribution field of the foundation is constructed. Obtain pipeline burial depth information, combine the continuous settlement distribution field of the foundation and the characteristics of the settlement area, calculate the pipeline axis offset and bending radius change, determine the geometric shape change of the pre-buried cable pipeline, and generate the pipeline deformation surface; Based on the changes in the pipeline geometry, the connection method is determined. Gradient analysis and curvature calculation are performed on the deformed surface of the pipeline to extract local bending deformation and stress concentration areas. Combined with the connection method and ambient temperature, the internal stress distribution of the cable is determined. Based on the internal stress distribution of the cable, the alternating stress amplitude and stress concentration area are determined. Combined with the fatigue characteristic curve of the pipe material and the number of stress cycles, the wear degree of the sheath surface and the crack propagation rate are determined, and the probability of fatigue crack initiation of the sheath is statistically analyzed. Based on the probability of fatigue crack initiation of the sheath, the crack risk assessment result is determined, and the structural deformation corresponding to the material and geometry of the pipeline to be replaced is determined by combining the crack risk assessment result and the service life of the pipeline. The location of crack initiation is determined based on the internal stress distribution of the cable, the dynamic stress distribution of the cable path is determined in combination with the structural deformation, the trend of cable sheath crack propagation is predicted based on the alternating stress amplitude and the location of crack initiation, and the time of failure is determined. A maintenance plan is developed based on the time of the fault occurrence. The risk level of the pipe section is determined by combining the characteristics of the settlement area and the burial depth information of the pipeline. The priority of cable route maintenance is determined based on the crack propagation rate and the wear degree of the sheath surface.

[0004] Furthermore, the process of obtaining the height of the foundation from a preset horizontal plane, statistically analyzing the settlement rate, determining the characteristics of the settlement area by combining the characteristics of the foundation soil layers, geological conditions, and construction history, generating a continuous settlement distribution based on the settlement rate and the characteristics of the settlement area, determining the soil layer compression modulus, and constructing a continuous settlement distribution field for the foundation includes: The height of the foundation surface above a reference horizontal plane is collected using a sensor array. The settlement rate of each monitoring point is calculated based on the height difference between adjacent time periods, and the monitoring area is divided based on the settlement rate. For different settlement rate areas, soil samples are obtained, and the soil density, moisture content, and particle size distribution parameters are measured. Combined with geological survey and construction log data, a correspondence matrix between soil properties and the settlement rate is established. Based on the correspondence matrix and the settlement rate, a continuous settlement distribution is generated using interpolation. The compression of each soil layer is calculated based on the soil sample data. Based on the continuous settlement distribution and the load data in the construction log, stress and strain are calculated, the soil compression modulus is determined, and a continuous settlement distribution field of the foundation is constructed with coordinates as the index and settlement as the element.

[0005] Furthermore, the process of obtaining pipeline burial depth information, combining the continuous settlement distribution field of the foundation and the characteristics of the settlement area, calculating the pipeline axis offset and bending radius change, determining the geometric shape change of the pre-buried cable pipeline, and generating the pipeline deformation surface includes: The pipeline's three-dimensional coordinates and material properties are obtained from the database. The pipeline's centerline burial depth and initial spatial position are extracted. Based on the continuous settlement distribution field of the foundation, the vertical displacement of the pipeline is calculated, generating a spatial coordinate sequence of the deformed pipeline. Based on the spatial coordinate sequence of the deformed pipeline, the pipeline centerline is fitted, and the bending radius and axial offset at each point are calculated. Based on the bending radius and axial offset, the bending stress distribution of the pipeline section is determined. Based on the bending stress distribution and pipeline material properties, the pipe diameter change and wall thickness reduction are calculated, and the local indentation depth is determined based on the stress concentration area. Based on the pipe diameter change, the wall thickness reduction, and the local indentation depth, a three-dimensional data matrix with axial coordinates, circumferential angles, and radial deformation as parameters is constructed to generate the pipeline deformation surface.

[0006] The process of determining the connection method based on the pipeline's geometric changes, performing gradient analysis and curvature calculation on the pipeline's deformable surface, and extracting local bending deformation and stress concentration areas includes: Based on the pipe diameter change and bending radius in the pipeline geometry change, the connection method of the pipeline joint is determined, and the corresponding axial stiffness and bending stiffness are extracted; the deformation gradient field and curvature distribution of the pipeline deformation surface are calculated, the local bending deformation is determined based on the curvature distribution, and the stress concentration area is identified based on the deformation gradient field.

[0007] Furthermore, the determination of alternating stress amplitude and stress concentration areas based on the internal stress distribution of the cable, combined with the fatigue characteristic curve of the pipe material and the number of stress cycles, to determine the wear degree and crack propagation rate of the sheath surface includes: Based on the time series of the internal stress distribution of the cable, the maximum and minimum stress values ​​are extracted, the alternating stress amplitude is calculated, and the stress concentration area is determined based on the material fatigue limit value. Based on the alternating stress amplitude and the stress concentration area, the allowable number of cycles is calculated in conjunction with the fatigue life curve, and the actual number of stress cycles is calculated based on the monitoring data. Based on the actual number of stress cycles and the allowable number of cycles, the damage accumulation degree is calculated, and the wear degree of the sheath surface and the crack propagation rate are determined based on the damage accumulation degree.

[0008] Furthermore, the step of determining the crack risk assessment result based on the fatigue crack initiation probability of the sheath, and combining the crack risk assessment result with the service life of the pipeline to determine the structural deformation corresponding to the material and geometry of the pipeline to be replaced, includes: Based on the comparison between the probability of fatigue crack initiation of the sheath and the risk classification standard, the crack risk assessment result is determined; based on the crack risk assessment result and the service life of the pipeline, the pipeline material is determined; based on the pipeline material and the stress value in the stress concentration area, the expected strain value is calculated, and the pipeline inner diameter specification, wall thickness and bending degree are determined; based on the pipeline inner diameter specification, the wall thickness and the bending degree, combined with the continuous settlement distribution field of the foundation, the radial deformation, axial displacement and bending deformation are calculated to form a structural deformation dataset.

[0009] Furthermore, determining the crack initiation location based on the internal stress distribution of the cable and determining the dynamic stress distribution along the cable path in conjunction with the structural deformation includes: Based on the internal stress distribution of the cable, the stress gradient and stress concentration factor are calculated to determine the crack initiation location; based on the crack initiation location and the structural deformation, the cable path displacement change and dynamic strain rate are calculated to determine the dynamic stress distribution of the cable path.

[0010] Furthermore, the process of formulating a maintenance plan based on the time of the fault occurrence, determining the risk level of the pipe section by combining the characteristics of the settlement area and the pipe burial depth information, and determining the maintenance priority ranking of the cable route based on the crack propagation rate and the degree of wear on the sheath surface, includes: The remaining safe time window is calculated based on the time of the fault occurrence, the maintenance execution time limit is determined, and a maintenance plan is generated; the stress growth rate of the pipe section is calculated based on the characteristics of the settlement area and the burial depth information of the pipeline, and the risk level of the pipe section is determined; based on the risk level of the pipe section, the crack propagation rate, and the wear degree of the sheath surface, a comprehensive hazard index is calculated, and the priority ranking of cable route maintenance is determined.

[0011] The technical solutions provided by the embodiments of the present invention may include the following beneficial effects: This invention discloses a big data-based method for analyzing and assessing electrical safety risks in buildings. Addressing issues such as geometric deformation, stress concentration, and sheath fatigue cracking in cable ducts caused by foundation settlement, the method integrates factors such as foundation settlement rate, soil characteristics, duct burial depth, and service life to construct a continuous settlement distribution field. It calculates duct axis offset and bending radius changes to generate deformation surfaces, then analyzes local stress concentration and alternating stress amplitude. Combining material fatigue characteristics, it predicts crack initiation probability and propagation trends, determines failure time windows, and finally prioritizes maintenance based on risk level and crack propagation rate. This invention, through multi-dimensional data coupling and dynamic stress analysis, accurately predicts cable sheath failure risks, optimizes maintenance resource allocation, and improves the reliability and safety of cable system operation. Attached Figure Description

[0012] Figure 1This is a flowchart of a building electrical safety risk analysis and assessment method based on big data according to the present invention.

[0013] Figure 2 This is a schematic diagram of a building electrical safety risk analysis and assessment method based on big data according to the present invention. Detailed Implementation

[0014] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0015] like Figure 1-2 This embodiment of a big data-based building electrical safety risk analysis and assessment method may specifically include: Step S101: Continuously obtain the height between the foundation and the preset horizontal plane, count the settlement rate, determine the characteristics of the settlement area by obtaining the characteristics of the foundation soil layer, geological conditions and construction history, obtain the continuous settlement distribution based on the settlement rate and regional characteristics, determine the soil layer compression modulus, and obtain the continuous settlement distribution field of the foundation.

[0016] A laser ranging sensor array is deployed on the foundation surface. At each monitoring point, the height between the foundation surface and the reference horizontal plane is collected at preset time intervals. The settlement rate of each monitoring point is calculated by dividing the height difference between adjacent time periods by the time interval. The monitoring area is initially divided based on the settlement rate. For areas with different settlement rates, soil samples at various depths are obtained using borehole sampling. Soil density, moisture content, and particle size distribution parameters are determined through indoor geotechnical tests. Combined with stratigraphic distribution information from the geological survey report and historical loading data from the construction log, a correspondence matrix between soil properties and settlement rate is established. Based on the correspondence matrix and the settlement rate data from each monitoring point, Kriging interpolation is used to spatially interpolate the areas between monitoring points, obtaining the continuous settlement distribution across the entire foundation area. The thickness of each soil layer is obtained from the borehole sampling data, and the compression of each soil layer is calculated by the ratio of settlement to the corresponding soil layer thickness. Based on the compression of each soil layer and the load data applied to the foundation surface obtained from the construction log, the stress σ is obtained by dividing the load by the bearing area of ​​the foundation, and the strain ε is obtained by dividing the compression by the initial thickness of the soil layer. The compression modulus values ​​of soil layers at different depths are determined according to the compression modulus calculation formula E=σ / ε. Combining the continuous settlement distribution and the spatial variation law of the compression modulus, a continuous settlement distribution field of the foundation is constructed with coordinate position as index and settlement value as element.

[0017] Specifically, the deployment of laser ranging sensor arrays needs to take into account the geometry of the foundation and the expected settlement area.

[0018] In one possible implementation, sensors are arranged in a grid pattern, typically spaced 5-10 meters apart, with increased density in areas of concentrated building load. Each sensor emits a laser beam vertically downwards onto the foundation surface, and the distance is calculated by measuring the round-trip time of the laser. The reference horizontal plane is usually selected as a benchmark point on a stable bedrock surface or deep soil layer far from the settlement influence zone. This layout comprehensively captures the spatial deformation characteristics of the foundation, avoiding the omission of localized abnormal settlement. The calculation of the settlement rate involves processing time-series data.

[0019] Specifically, if the height of a monitoring point is h1 at time t1 and h2 at time t2, then the settlement rate during that period is v = (h1 - h2) / (t2 - t1). Settlement rate data obtained through continuous monitoring can identify rapid settlement zones, slow settlement zones, and stable zones. This zoning provides a basis for subsequent targeted investigations, making resource allocation more rational. The drilling depth needs to penetrate the entire compressible soil layer until reaching the relatively stable bearing layer. In geotechnical testing, density is determined using the ring cutter method, moisture content is determined by the drying method, and particle size distribution is determined using a combination of sieve analysis and densitometer methods.

[0020] It should be noted that these soil layer parameters are intrinsically related to settlement rates: soft clay layers with high water content tend to have larger settlement rates, while dense sand layers have smaller settlement rates. Loading history recorded in the construction log, such as foundation pouring time and superstructure construction progress, directly affects the degree of soil consolidation. The establishment of the matrix relating soil layer properties to settlement rates is based on statistical analysis of a large amount of measured data.

[0021] For example, when the soil layer is silty clay, the water content exceeds the liquid limit, and the overlying load reaches a preset threshold, the settlement rate increases significantly. This correspondence provides a physical basis for subsequent spatial interpolation, making the interpolation results not only mathematically reasonable but also consistent with the laws of soil mechanics. Kriging interpolation has unique advantages in processing foundation settlement data. This method considers the spatial correlation of the data, using a variogram to describe the degree of correlation between data at different distances.

[0022] In one embodiment, the experimental variogram is first calculated, then a theoretical variogram model is fitted, and finally, the estimated settlement value and its error for the unmeasured points are obtained. This method generates a continuous settlement distribution that not only provides the spatial variation law of settlement but also gives information on the estimation accuracy. The process of determining the compressive modulus reflects the essence of the stress-strain relationship.

[0023] Preferably, the stress σ is obtained by dividing the load on the foundation surface by the effective bearing area, taking into account the load diffusion effect. The strain ε is the ratio of compression to the initial thickness of the soil layer, reflecting the relative deformation of the soil. The compression modulus obtained in this way can accurately reflect the compression characteristics of soil layers at different depths, providing reliable parameters for engineering design. The continuous settlement distribution field of the foundation is stored using a three-dimensional data structure, indexed by plane coordinates (x, y) and depth z, with the settlement s as the numerical value. This data organization method facilitates subsequent visualization and engineering applications, such as generating settlement contour maps and calculating differential settlement. By establishing such a distribution field, the overall deformation state of the foundation can be accurately grasped, allowing for timely reinforcement measures to ensure the safe use of buildings.

[0024] Step S102: Obtain information on different pipeline burial depths, combine the continuous settlement distribution field of the foundation and the characteristics of the settlement area, calculate the pipeline axis offset and bending radius change, determine the geometric shape change of the pre-buried cable pipeline, and generate the pipeline deformation surface.

[0025] By reading the pipeline's three-dimensional coordinate data and material properties from a geographic information database, the burial depth, initial spatial position, elastic modulus, and yield strength of each point along the pipeline's centerline are obtained. Based on the settlement data of the corresponding coordinate positions in the continuous settlement distribution field of the foundation, the vertical displacement of each point along the pipeline is calculated, resulting in a deformed pipeline spatial coordinate sequence. Based on this deformed spatial coordinate sequence, the pipeline centerline is fitted using cubic spline interpolation. The bending radius of each point is obtained by calculating the radius of the arc formed by three adjacent points. The axial offset is determined by comparing the lateral displacement of the pipeline centerline before and after deformation. The bending stress distribution of each section of the pipeline is calculated based on the reciprocal of the bending radius and the axial offset. Based on the bending stress distribution of each section of the pipeline and the elastic modulus of the pipeline material obtained from the database, the strain value is calculated by dividing the stress by the elastic modulus. The change in pipe diameter is obtained by multiplying the strain value by the original pipeline radius. The degree of wall thickness reduction is determined by multiplying the ratio of the bending stress value to the material yield strength by the original wall thickness. If the local bending stress value exceeds a preset threshold, the local depression depth at that location is calculated based on the stress concentration factor. Based on data on pipe diameter changes, wall thickness reduction, and local depression depth, a three-dimensional data matrix is ​​constructed with the pipe axial coordinate as the horizontal axis, the circumferential angle as the vertical axis, and the radial deformation as the elevation value. By performing bilinear interpolation on discrete data points, the deformation value at the intermediate position is calculated, generating a continuous pipe deformation surface.

[0026] Specifically, pipeline data stored in geographic information databases typically contains information from multiple layers.

[0027] In one possible implementation, the three-dimensional coordinates of the pipeline are recorded as equally spaced sampling points, each containing longitude, latitude, and elevation information. Material property parameters are stored in a separate property table, including mechanical parameters such as elastic modulus, yield strength, and Poisson's ratio. When foundation settlement occurs, the vertical displacement of each point on the pipeline is obtained through interpolation: first, the corresponding grid of the pipeline sampling point in the foundation settlement distribution field is found; then, bilinear interpolation is performed based on the settlement values ​​of the grid vertices to obtain the accurate settlement amount at that point. Cubic spline interpolation exhibits good smoothness when processing the pipeline centerline.

[0028] Specifically, this method constructs a piecewise cubic polynomial, ensuring the continuity of position, first derivative, and second derivative at the connection points of adjacent segments. This continuity guarantees that the fitted pipe centerline has no abrupt changes, conforming to the physical characteristics of actual pipes. The calculation of the bending radius is based on the principles of differential geometry: at any point on the curve, an arc can be determined through that point and its two adjacent points; the radius of this arc is the bending radius at that point. The smaller the bending radius, the greater the degree of pipe bending, and the greater the bending stress generated.

[0029] It should be noted that the stress generated in the pipeline under foundation settlement mainly originates from bending deformation. When the pipeline bends, the outer side experiences tensile stress, and the inner side experiences compressive stress; the magnitude of the stress is inversely proportional to the bending radius. The presence of axial misalignment will further exacerbate this stress concentration phenomenon.

[0030] For example, when a section of a pipeline bends into an S-shape due to uneven settlement, the stress value at the bend inflection point will increase significantly.

[0031] In one embodiment, when the pipe cross-section is subjected to bending stress, according to Hooke's Law, strain equals stress divided by the elastic modulus. This strain acts radially on the pipe, causing the pipe cross-section to change from a circle to an ellipse. The change in pipe diameter is the difference between the major axis of the ellipse and the original diameter. The assessment of the degree of wall thickness reduction is based on the theory of plastic deformation: when the stress exceeds a certain proportion of the material's yield strength, the pipe wall begins to undergo irreversible plastic deformation, resulting in a permanent reduction in wall thickness. The calculation of the depth of local indentations involves the concept of stress concentration factor.

[0032] Preferably, the stress concentration factor is obtained through finite element analysis or empirical formulas, reflecting the degree of stress amplification at geometric discontinuities. When the pipeline has initial defects or is subjected to local loads, the actual stress at that location is the nominal stress multiplied by the stress concentration factor. If the actual stress exceeds the material's critical buckling stress, the pipe wall will experience local instability, forming an inward indentation. The generation process of the pipeline deformation surface employs data visualization techniques. In the three-dimensional data matrix, each data point represents the radial deformation at a certain location on the pipeline surface. Bilinear interpolation calculates the deformation value at any point within the rectangular area using the known values ​​of the four corner points, thus transforming discrete measurement data into a continuous surface.

[0033] Step S103: Determine the connection method based on the pipeline geometry, perform gradient analysis and curvature calculation on the pipeline deformation surface, extract local bending deformation and stress concentration areas, and determine the internal stress distribution of the cable in combination with the connection method and ambient temperature.

[0034] Based on the pipe diameter change and bending radius data in the pipe deformation surface, the geometric parameters of the pipe joint location are identified. If the bending radius is less than a preset threshold, it is determined to be a flexible connection; otherwise, it is determined to be a rigid connection. The axial stiffness and bending stiffness values ​​of the corresponding connection type are retrieved from the pipe design document as mechanical transfer coefficients. Spatial partial derivatives are calculated for the pipe deformation surface to obtain the deformation gradient field. By taking partial derivatives again on the deformation gradient field and calculating its determinant, the curvature distribution is obtained. The local bending deformation is determined based on the region where the curvature value exceeds the critical value. The stress concentration region is identified by combining the location of the gradient value abruptly changing in the deformation gradient field. Based on the local bending deformation, the location of the stress concentration region, and the mechanical transfer coefficient of the connection type, the mechanical stress transmitted from the inner wall of the pipe to the cable surface is calculated by multiplying the bending deformation by the pipe stiffness and then by the mechanical transfer coefficient. The ambient temperature is read from the temperature recorder. The thermal strain is calculated by multiplying the thermal expansion coefficient in the cable sheath material data table by the difference between the ambient temperature and the reference temperature. The thermal stress is obtained by multiplying the thermal strain by the material's elastic modulus. The total stress borne by the outer sheath of the cable is determined by the superposition of mechanical stress and thermal stress. Combined with the thickness of each layer and the elastic modulus of the material obtained from the cable specification, the stress transmission is calculated layer by layer using the finite difference method. The stress attenuation coefficient between layers is determined by the ratio of the elastic modulus of two adjacent layers, thus obtaining the internal stress distribution of the cable from the outer sheath to the conductor core.

[0035] Specifically, the determination of the pipe connection method is based on the key parameter of bending radius.

[0036] In one possible implementation, flexible connections typically employ rubber joints or bellows compensators, characterized by allowing for larger angular and axial displacements. When the bending radius is less than six times the pipe diameter, rigid connections generate excessive additional stress, at which point the system determines that a flexible connection is necessary. Rigid connections often use flanges or welding, suitable for sections with minimal deformation. The mechanical transfer coefficient reflects the force transmission capacity of the connection; the axial stiffness of a flexible connection is typically 1 / 10 to 1 / 20 that of a rigid connection, and this difference directly affects the magnitude of the mechanical stress borne by the cable. The calculation of the deformation gradient field involves partial derivative operations in multidimensional space.

[0037] Specifically, for any point on the deformable surface of the pipe, its deformation gradient is obtained by calculating the partial derivatives of the displacement at that point in the three coordinate directions. This 3×3 matrix contains all the deformation information for that point. The calculation of curvature requires taking the second derivative of the deformation gradient field, which essentially involves calculating the Gaussian curvature and mean curvature of the surface. When the curvature value increases sharply, it indicates a significant geometric discontinuity in the region, often corresponding to stress concentration.

[0038] It should be noted that the identification of stress concentration regions depends not only on curvature analysis, but also on the abrupt changes in the deformation gradient field.

[0039] For example, at pipe bends, even with a large designed curvature, if the deformation gradient field indicates additional torsional or compressive deformation, it will still be marked as a stress concentration area. This comprehensive judgment method improves the accuracy of identification. The calculation process of mechanical stress reflects the basic principles of structural mechanics. The bending deformation of the pipe generates bending stress in the pipe wall, which is transmitted to the cable surface through the inner wall of the pipe. The transmission efficiency depends on the mechanical transmission coefficient of the connection method.

[0040] For example, in a rigid connection, almost all the stress in the conduit is transferred to the cable; while in a flexible connection, some deformation energy is absorbed, reducing the amount of stress transferred. Thermal stress arises from the thermal expansion and contraction properties of materials. When the ambient temperature rises by 30 degrees Celsius, the polyethylene sheath material will expand significantly, but it cannot expand or contract freely due to the confinement of the conduit, thus generating compressive stress.

[0041] In one embodiment, the application of the finite difference method makes stress analysis of complex multilayer structures feasible. A typical cable structure includes an outer sheath, a metallic sheath, an insulation layer, and a conductor core, with the elastic moduli of each layer differing by up to two orders of magnitude. As stress propagates from the outside in, partial reflection and transmission occur at each interface. The interlayer stress attenuation coefficient is calculated by the ratio of the elastic moduli of adjacent layers; the greater the difference in elastic moduli, the more significant the attenuation. The resulting internal stress distribution of the cable exhibits a clear radial gradient characteristic. The outer sheath bears the maximum stress, decreasing layer by layer inwards, with the lowest stress at the conductor core. This distribution pattern is of great significance for the long-term operational reliability assessment of cables, as high-stress areas are more prone to material aging and fatigue failure.

[0042] Step S104: By analyzing the internal stress distribution of the cable, the alternating stress amplitude and stress concentration area are determined. Based on the alternating stress amplitude and stress concentration area, the fatigue characteristic curve of the pipe material and the number of stress cycles are analyzed to determine the wear degree of the sheath surface and the crack propagation rate, and the probability of fatigue crack initiation of the sheath is statistically obtained.

[0043] Based on the time-series data of the internal stress distribution of the cable, the maximum and minimum stress values ​​for each monitoring cycle are extracted. The alternating stress amplitude is obtained by dividing the difference between the maximum and minimum values ​​by two. The fatigue limit value is then retrieved from the sheath material handbook, and the location where the alternating stress amplitude exceeds the fatigue limit value is identified as a stress concentration area. Based on the alternating stress amplitude and the location of the stress concentration area, the slope coefficient and intercept coefficient of the fatigue life curve are read from the pipe material test report. The logarithmic number of cycles is calculated by multiplying the logarithm of the stress amplitude by the slope coefficient and adding the intercept coefficient. The allowable number of cycles is obtained through antilogarithmic calculation, and the actual number of stress cycles is calculated by combining the load change frequency recorded by the monitoring system. The damage accumulation degree is calculated based on the ratio of the actual number of stress cycles to the allowable number of cycles. The wear degree of the sheath surface is obtained by multiplying the damage accumulation degree by the wear rate coefficient determined by the sheath material experiment. If the damage accumulation degree exceeds the preset crack initiation threshold, the crack propagation rate is calculated as the material constant multiplied by the power of the stress intensity factor amplitude. Based on the wear degree and crack propagation rate data of the sheath surface, a two-parameter Weibull distribution is used to fit the fatigue failure time. The probability of fatigue crack initiation in the sheath within a specified operating time is calculated using shape and dimensional parameters, as shown in the formula: F(t) represents the probability of fatigue crack initiation in the sheath within time t, where t represents the running time, η represents the scale parameter of the Weibull distribution, and β represents the shape parameter of the Weibull distribution.

[0044] Specifically, the extraction of alternating stress amplitude reflects the dynamic load characteristics that the cable bears in actual operation.

[0045] In one possible implementation, the stress monitoring system records stress values ​​every 10 minutes, forming a continuous time series. The cable stress fluctuates around the average value due to local temperature changes or vibrations from passing vehicles. The maximum stress may reach 50 MPa, and the minimum stress may drop to 30 MPa, resulting in an alternating stress amplitude of 10 MPa. This amplitude directly determines the material's fatigue damage rate. The fatigue limit is an inherent property of the material, characterizing the maximum stress amplitude at which the material can withstand an unlimited number of cycles without fatigue failure. The fatigue limit of polyethylene sheathing materials is typically 30% to 40% of its tensile strength. When the alternating stress amplitude in a certain area exceeds this limit, that area becomes a potential failure point and requires close monitoring.

[0046] It should be noted that the fatigue life curve was established based on a large amount of material test data.

[0047] Specifically, under laboratory conditions, cyclic stresses of different amplitudes are applied to standard specimens, and the number of cycles at which fracture occurs is recorded. After taking the logarithm of both the stress amplitude and the number of cycles, the data points show a essentially linear relationship. The slope coefficient reflects the material's sensitivity to stress changes, while the intercept coefficient is related to the material's basic fatigue strength. This curve can be used to predict fatigue life at any stress level. Determining the frequency of load changes requires considering the superimposed effects of multiple factors.

[0048] For example, temperature-induced daily cycles occur once a day, vehicle vibrations can reach tens of times per hour, and wind loads cause even higher vibration frequencies. The superposition of these different frequency loads creates a complex stress spectrum. The actual number of stress cycles is the result of the accumulation of various frequency components. The calculation of damage accumulation follows the linear cumulative damage theory. When the accumulation reaches 0.3, microcracks begin to appear inside the material; at 0.7, cracks begin to propagate; and near 1.0, fracture failure is imminent. The wear rate coefficient is determined through accelerated aging tests and reflects the relationship between the degree of damage and the surface wear depth.

[0049] In one embodiment, the calculation of crack propagation rate involves principles of fracture mechanics. The stress intensity factor amplitude comprehensively considers the effects of stress level, crack size, and geometry. Material constants and power exponents are determined through crack propagation experiments, and their values ​​vary considerably among different materials.

[0050] For example, the power exponent for tough materials is typically between 2 and 4, while for brittle materials it may exceed 6. The Weibull distribution is particularly well-suited for describing the randomness of fatigue failure. A shape parameter less than 1 indicates a higher early failure rate, while a value greater than 3.5 approximates a normal distribution. The scale parameter is related to the mean life and reflects the overall reliability level. The probability of crack initiation within the design life is calculated, providing a quantitative basis for maintenance decisions. This probabilistic assessment method considers the dispersion of material properties and the uncertainty of loads, making it more consistent with engineering realities than deterministic methods.

[0051] Step S105: Determine the crack risk assessment result based on the probability of fatigue crack initiation in the sheath, and determine the material and corresponding structural deformation of the pipeline to be replaced based on the crack risk assessment result and the service life of the pipeline.

[0052] Based on the probability of fatigue crack initiation in the sheath, the probability value is compared with the threshold in the risk classification standard. If the probability exceeds the first risk threshold, it is marked as Level 3 risk; if it is between the first and second risk thresholds, it is marked as Level 2 risk; otherwise, it is marked as Level 1 risk, thus obtaining the crack risk assessment result. Based on the crack risk assessment result and the pipeline service life data read from the pipeline archive, if the risk assessment result is Level 3 and the service life exceeds the preset service life threshold, it is determined that the pipeline needs to be replaced immediately, and high-strength alloy steel is selected from the material database. If the risk assessment result is Level 2, reinforced polyethylene is selected. According to the selected pipeline material, the corresponding elastic modulus and yield strength parameters are retrieved from the design parameter library. Combined with the maximum stress value of the pipeline stress concentration area obtained previously, the expected strain value is calculated by dividing the maximum stress value by the elastic modulus. Based on the expected strain value and material characteristics, the inner diameter specification, wall thickness value, and bending limit of the new pipeline are determined. Based on the determined pipe inner diameter specifications, wall thickness values, and bending limits, and combined with the previously obtained foundation continuous settlement distribution field data, the radial deformation, axial displacement, and bending deformation of the new pipe under settlement are obtained through finite element calculation, forming the corresponding structural deformation dataset.

[0053] Specifically, the risk grading standards are developed based on a comprehensive analysis of industry experience and statistical data.

[0054] In one possible implementation, the first risk threshold is typically set at 0.1% of the crack initiation probability, meaning there is a 10% chance of a crack appearing; the second risk threshold is set at 0.05%. This grading method allows maintenance resources to be prioritized for high-risk areas. Level 3 risk indicates the need for immediate action, Level 2 risk requires enhanced monitoring, and Level 1 risk can be maintained according to routine cycles. The service life of pipelines is closely related to the degradation of material properties.

[0055] Specifically, pipelines exposed to underground environments are subjected to the combined effects of soil corrosion, stress cycling, and temperature changes over long periods, leading to a gradual decrease in material strength. As their service life nears its design life, even if their current condition is acceptable, the remaining safety margin is minimal. A comprehensive assessment, considering both risk level and performance, allows for proactive replacement before a failure occurs, preventing losses from sudden malfunctions.

[0056] It should be noted that material selection considers not only strength requirements but also economy and ease of construction. High-strength alloy steel possesses excellent mechanical properties, capable of withstanding greater stress without plastic deformation, making it suitable for high-risk areas. Its elastic modulus typically reaches 200 GPa, 200 times that of polyethylene. Reinforced polyethylene adds glass or carbon fibers to ordinary polyethylene, improving strength and stiffness while maintaining good corrosion resistance and flexibility. The design parameter database stores performance data for various pipe materials under different conditions. This data comes from technical manuals provided by material manufacturers and test reports from third-party testing institutions. The elastic modulus and yield strength obtained through querying are the fundamental parameters for stress-strain calculations. The calculation of the expected strain value follows Hooke's Law, reflecting the deformation characteristics of the material within its elastic range. The determination of pipe geometry parameters requires satisfying multiple constraints.

[0057] In one embodiment, the inner diameter specification must ensure sufficient space for cable laying, typically 1.5 to 2 times the cable's outer diameter. The wall thickness must strike a balance between load-bearing capacity and economy; excessive thickness increases cost and construction difficulty, while insufficient thickness fails to provide adequate structural strength. Bending limits are related to the material's ductility; the minimum bending radius for metal pipes is typically 10 to 15 times the pipe diameter, while for flexible materials it can reach 5 times. Finite element method (FEM) calculations play a crucial role in assessing the deformation of new pipes. This method discretizes the continuous pipe structure into a finite number of elements, each whose mechanical behavior can be described by simple equations. By assembling the equations of all elements to form an overall stiffness matrix, and applying boundary conditions caused by foundation settlement, the displacements and stresses at each node are obtained. Radial deformation reflects the ellipticity of the pipe's cross-section, axial displacement characterizes the pipe's expansion and contraction, and bending deformation corresponds to the curvature change of the pipe's centerline.

[0058] Step S106: Determine the crack initiation location by analyzing the internal stress distribution of the cable; determine the dynamic stress distribution along the cable path based on the adjusted structural deformation; and predict the crack propagation trend of the cable sheath by combining the alternating stress amplitude and the crack initiation location, thereby determining the time of failure.

[0059] Based on the internal stress distribution data of the cable, regions where the stress value exceeds the fatigue limit threshold of the sheath material are identified. The stress gradient is obtained by calculating the stress difference between adjacent points and dividing by the distance. The stress concentration factor is obtained by dividing the stress value at the maximum stress gradient by the average stress value. The coordinates of the location with the maximum stress concentration factor are determined as the crack initiation location. Based on the coordinates of the crack initiation location and the obtained structural deformation data, the displacement change at each point along the cable path is calculated through interpolation. The dynamic strain rate is calculated by dividing the displacement difference between adjacent moments by the time interval. The dynamic stress distribution along the cable path is obtained by multiplying the dynamic strain rate by the material's elastic modulus. Based on the stress value at the crack initiation location in the dynamic stress distribution along the cable path and the previously obtained alternating stress amplitude, the range of the stress intensity factor at the crack tip is calculated. Using Paris's law, which states that the crack propagation rate equals the material constant multiplied by a power of the stress intensity factor range, the propagation trend of the crack length over time is accumulated and calculated. Based on the crack propagation trend data, when the crack length reaches the sheath wall thickness, it is determined as a penetration failure. The time of failure is determined by the cumulative time corresponding to the crack length equaling the sheath wall thickness.

[0060] Specifically, the calculation of stress gradient reveals the spatial variation of stress.

[0061] In one possible implementation, adjacent measurement points are selected on the cable sheath surface, and the stress values ​​at each point are recorded. The stress difference between any two adjacent points is then calculated and divided by the distance between them. When the stress rapidly increases from 30 MPa to 50 MPa, with a distance of only 2 mm, the stress gradient reaches 10 MPa / mm. This high-gradient region is often where the material is most prone to fatigue failure. The stress concentration factor reflects the degree of amplification of local stress relative to the average stress.

[0062] Specifically, stress is significantly higher in areas where pipes bend, joints are made, or geometry changes abruptly than in the surrounding area.

[0063] For example, when the average stress is 20 MPa, the actual stress at some local locations may reach 60 MPa, in which case the stress concentration factor is 3. The larger this factor is, the more likely that location is to become a crack initiation point.

[0064] It is important to note that the concept of dynamic strain rate is crucial for understanding the real-time stress state of a cable. As the foundation continues to settle, the position of each point on the cable changes continuously over time. By comparing the displacement at adjacent moments, the deformation rate can be calculated.

[0065] For example, if a point displaces downwards by 5 mm in one hour, the strain rate is that displacement divided by the original cable length and then divided by time. Multiplying this strain rate by the material's elastic modulus gives the dynamic stress value. The main difference between dynamic stress distribution and static stress is that the time factor is considered.

[0066] In one embodiment, thermal expansion and contraction caused by temperature changes induce periodic stress variations in the cable. During the day, as temperatures rise, the cable expands under constraint, generating compressive stress; at night, as temperatures drop, tensile stress is generated. This dynamic change in stress accelerates the fatigue damage process of the material. Paris's law is a classic theory describing fatigue crack propagation. This law states that the crack propagation rate has a power function relationship with the range of the stress intensity factor. The stress intensity factor comprehensively considers the effects of stress level, crack size, and geometric factors. When the crack length is 1 mm and the stress range is 30 MPa, the stress intensity factor is calculated using specific geometric correction factors. The material constants and power exponents are determined experimentally and vary greatly among different materials. The prediction of crack propagation trends is based on the principle of cumulative damage.

[0067] Preferably, starting from the initial microcrack, each stress cycle causes the crack to grow by a certain length. By gradually accumulating these increments, a crack length versus time curve can be obtained. Initially, crack propagation is slow, but once the crack length exceeds a certain critical value, the propagation rate accelerates dramatically, exhibiting exponential growth. The determination of the failure time depends on the selection of the failure criterion. When the crack completely penetrates the sheath wall thickness, the cable's sealing performance is lost, and the intrusion of moisture and contaminants leads to insulation failure.

[0068] For example, in a cable with a 3mm sheath thickness, a crack depth of 3mm is considered a penetration failure. Crack propagation curves can accurately predict the time required to reach this depth, providing a scientific basis for developing maintenance plans.

[0069] Step S107: Develop an emergency maintenance plan based on the fault occurrence time window, combine the burial depth information of different pipelines to obtain the risk level assessment of each pipeline section, and determine the maintenance priority ranking of the cable route by combining the crack propagation rate and the degree of surface wear.

[0070] Based on the determined fault occurrence time, the difference between the fault time and the current time is calculated to obtain the remaining safe time window. If the remaining safe time window is less than a preset emergency threshold, it is marked as an emergency maintenance task. The maintenance execution time limit is determined according to the length of the remaining safe time window, generating an emergency maintenance plan that includes the pipe segment number and execution time limit. Based on the pipe segment number in the emergency maintenance plan, the soil compression modulus and settlement rate of the corresponding pipe segment are extracted. Combined with the burial depth information of different pipelines, the depth correction coefficient is obtained by dividing the burial depth value by the standard depth. The stress growth rate of the pipe segment is obtained by multiplying the settlement rate by the depth correction coefficient and then dividing it by the soil compression modulus. The risk level assessment of each pipe segment is obtained based on the stress growth rate value. Based on the risk level assessment results of each pipe segment, combined with the crack propagation rate and surface wear degree data obtained previously, the crack hazard score is obtained by multiplying the risk level assessment value by the crack propagation rate. The wear hazard score is obtained by dividing the surface wear degree by the maximum wear threshold. The crack hazard score and the wear hazard score are added to obtain the comprehensive hazard index. The cable route maintenance priority is determined by arranging them from largest to smallest according to the comprehensive hazard index.

[0071] Specifically, the calculation of the remaining safe time window reflects the core concept of preventative maintenance.

[0072] In one possible implementation, if a pipe section is predicted to fail in 180 days, and 120 days have already passed, the remaining safe time window is 60 days. The emergency threshold is typically set at 90 days, a threshold determined by comprehensively considering maintenance resource allocation time, construction preparation period, and safety redundancy. When the remaining time is less than this threshold, the system automatically triggers the emergency maintenance process to avoid losses from reactive repairs. The maintenance execution timeframe follows the principle of risk and resource balance.

[0073] Specifically, the shorter the remaining time, the more urgent the execution deadline.

[0074] For example, a section of pipe with 30 days remaining needs to be maintained within 7 days, while a section with 60 days remaining can be scheduled within 15 days. This differentiated timeframe ensures that high-risk areas are prioritized while allowing maintenance teams reasonable preparation time.

[0075] It should be noted that the depth correction factor reflects the influence of burial depth on the stress on the pipeline. The standard depth is usually taken as 1.5 meters, which is a reference value determined based on extensive engineering experience. When the actual burial depth is 3 meters, the depth correction factor is 2, meaning that the earth pressure at this depth is twice that at the standard depth. Deep pipelines bear a greater weight of overburden, but are also subject to more stable constraints; this dual effect is reflected in the correction factor. The calculation of the stress growth rate of the pipeline segment reveals the intrinsic relationship between settlement and stress.

[0076] In one embodiment, in an area with a settlement rate of 10 mm per year, if the soil compression modulus is 5 MPa and the depth correction factor is 1.5, the stress growth rate is 3 MPa / year. This value directly reflects the accumulation rate of pipeline stress and is a key indicator for assessing long-term safety. The smaller the compression modulus, the weaker the soil, and the greater the additional stress generated under the same settlement. A graded quantitative method is used for risk level assessment.

[0077] Preferably, a stress growth rate exceeding 5 MPa / year is classified as high risk, 3-5 MPa / year as medium risk, and below 3 MPa / year as low risk. This classification is not a simple numerical division, but rather determined based on a comprehensive assessment of material fatigue characteristics and engineering safety factors. The fatigue life consumption rate of high-risk pipe sections is several times that of low-risk pipe sections. The construction of the comprehensive hazard index embodies the concept of multi-factor coupled assessment. The crack hazard score focuses on the dynamic deterioration of structural integrity, while the wear hazard score reflects the static degradation of surface protection capabilities.

[0078] For example, if a pipe section has a risk level of 3 and a crack propagation rate of 0.1 mm / day, its crack hazard score is 0.3. If the surface wear is 1.5 mm and the maximum wear threshold is 2 mm, the wear hazard score is 0.75. Adding these two together gives a comprehensive hazard index of 1.05. The significance of maintenance priority ranking lies in optimizing resource allocation. Pipe sections with the highest comprehensive hazard index are maintained first, ensuring that limited maintenance resources are used to their maximum effectiveness. Through scientific priority management, cable failure rates can be significantly reduced and power supply reliability improved without changing the overall maintenance cost.

[0079] The above are only some preferred embodiments of the present invention, but the present invention is not limited thereto, and many improvements and modifications can be made. Any improvements and modifications made based on the basic principles of the present invention should be considered to fall within the protection scope of the present invention.

Claims

1. A method for analyzing and assessing building electrical safety risks based on big data, characterized in that, The method includes: The height of the foundation from the preset horizontal plane is obtained, the settlement rate is statistically analyzed, and the characteristics of the settlement area are determined by combining the characteristics of the foundation soil layer, geological conditions and construction history. Based on the settlement rate and the characteristics of the settlement area, a continuous settlement distribution is generated, the soil layer compression modulus is determined, and a continuous settlement distribution field of the foundation is constructed. Obtain pipeline burial depth information, combine the continuous settlement distribution field of the foundation and the characteristics of the settlement area, calculate the pipeline axis offset and bending radius change, determine the geometric shape change of the pre-buried cable pipeline, and generate the pipeline deformation surface; Based on the changes in the pipeline geometry, the connection method is determined. Gradient analysis and curvature calculation are performed on the deformed surface of the pipeline to extract local bending deformation and stress concentration areas. Combined with the connection method and ambient temperature, the internal stress distribution of the cable is determined. Based on the internal stress distribution of the cable, the alternating stress amplitude and stress concentration area are determined. Combined with the fatigue characteristic curve of the pipe material and the number of stress cycles, the wear degree of the sheath surface and the crack propagation rate are determined, and the probability of fatigue crack initiation of the sheath is statistically analyzed. Based on the probability of fatigue crack initiation of the sheath, the crack risk assessment result is determined, and the structural deformation corresponding to the material and geometry of the pipeline to be replaced is determined by combining the crack risk assessment result and the service life of the pipeline. The location of crack initiation is determined based on the internal stress distribution of the cable, the dynamic stress distribution of the cable path is determined in combination with the structural deformation, the trend of cable sheath crack propagation is predicted based on the alternating stress amplitude and the location of crack initiation, and the time of failure is determined. A maintenance plan is developed based on the time of the fault occurrence. The risk level of the pipe section is determined by combining the characteristics of the settlement area and the burial depth information of the pipeline. The priority of cable route maintenance is determined based on the crack propagation rate and the wear degree of the sheath surface.

2. The method for analyzing and assessing building electrical safety risks based on big data according to claim 1, characterized in that, The process of obtaining the height of the foundation from a preset horizontal plane, statistically analyzing the settlement rate, determining the characteristics of the settlement area by combining the characteristics of the foundation soil layers, geological conditions, and construction history, generating a continuous settlement distribution based on the settlement rate and the characteristics of the settlement area, determining the soil layer compression modulus, and constructing a continuous settlement distribution field for the foundation includes: The height of the foundation surface above a reference horizontal plane is collected using a sensor array. The settlement rate of each monitoring point is calculated based on the height difference between adjacent time periods, and the monitoring area is divided based on the settlement rate. For different settlement rate areas, soil samples are obtained, and the soil density, moisture content, and particle size distribution parameters are measured. Combined with geological survey and construction log data, a correspondence matrix between soil properties and the settlement rate is established. Based on the correspondence matrix and the settlement rate, a continuous settlement distribution is generated using interpolation. The compression of each soil layer is calculated based on the soil sample data. Based on the continuous settlement distribution and the load data in the construction log, stress and strain are calculated, the soil compression modulus is determined, and a continuous settlement distribution field of the foundation is constructed with coordinates as the index and settlement as the element.

3. The method for analyzing and assessing building electrical safety risks based on big data according to claim 1, characterized in that, The process of obtaining pipeline burial depth information, combining the continuous settlement distribution field of the foundation and the characteristics of the settlement area, calculating the pipeline axis offset and bending radius change, determining the geometric shape change of the pre-buried cable pipeline, and generating the pipeline deformation surface includes: The pipeline's three-dimensional coordinates and material properties are obtained from the database. The pipeline's centerline burial depth and initial spatial position are extracted. Based on the continuous settlement distribution field of the foundation, the vertical displacement of the pipeline is calculated, generating a spatial coordinate sequence of the deformed pipeline. Based on the spatial coordinate sequence of the deformed pipeline, the pipeline centerline is fitted, and the bending radius and axial offset at each point are calculated. Based on the bending radius and axial offset, the bending stress distribution of the pipeline section is determined. Based on the bending stress distribution and pipeline material properties, the pipe diameter change and wall thickness reduction are calculated, and the local indentation depth is determined based on the stress concentration area. Based on the pipe diameter change, the wall thickness reduction, and the local indentation depth, a three-dimensional data matrix with axial coordinates, circumferential angles, and radial deformation as parameters is constructed to generate the pipeline deformation surface.

4. The method for analyzing and assessing building electrical safety risks based on big data according to claim 1, characterized in that, The process of determining the connection method based on the pipeline's geometric changes, performing gradient analysis and curvature calculation on the pipeline's deformable surface, and extracting local bending deformation and stress concentration areas includes: Based on the pipe diameter change and bending radius in the pipeline geometry change, the connection method of the pipeline joint is determined, and the corresponding axial stiffness and bending stiffness are extracted; the deformation gradient field and curvature distribution of the pipeline deformation surface are calculated, the local bending deformation is determined based on the curvature distribution, and the stress concentration area is identified based on the deformation gradient field.

5. The method for analyzing and assessing building electrical safety risks based on big data according to claim 1, characterized in that, The determination of alternating stress amplitude and stress concentration areas based on the internal stress distribution of the cable, combined with the fatigue characteristic curve of the pipe material and the number of stress cycles, to determine the wear degree of the sheath surface and the crack propagation rate includes: Based on the time series of the internal stress distribution of the cable, the maximum and minimum stress values ​​are extracted, the alternating stress amplitude is calculated, and the stress concentration area is determined based on the material fatigue limit value. Based on the alternating stress amplitude and the stress concentration area, the allowable number of cycles is calculated in conjunction with the fatigue life curve, and the actual number of stress cycles is calculated based on the monitoring data. Based on the actual number of stress cycles and the allowable number of cycles, the damage accumulation degree is calculated, and the wear degree of the sheath surface and the crack propagation rate are determined based on the damage accumulation degree.

6. The method for analyzing and assessing building electrical safety risks based on big data according to claim 1, characterized in that, The process of determining the crack risk assessment result based on the fatigue crack initiation probability of the sheath, and combining the crack risk assessment result with the service life of the pipeline to determine the structural deformation corresponding to the material and geometry of the pipeline to be replaced, includes: Based on the comparison between the probability of fatigue crack initiation of the sheath and the risk classification standard, the crack risk assessment result is determined; based on the crack risk assessment result and the service life of the pipeline, the pipeline material is determined; based on the pipeline material and the stress value in the stress concentration area, the expected strain value is calculated, and the pipeline inner diameter specification, wall thickness and bending degree are determined; based on the pipeline inner diameter specification, the wall thickness and the bending degree, combined with the continuous settlement distribution field of the foundation, the radial deformation, axial displacement and bending deformation are calculated to form a structural deformation dataset.

7. The method for analyzing and assessing building electrical safety risks based on big data according to claim 1, characterized in that, The process of determining the crack initiation location based on the internal stress distribution of the cable and determining the dynamic stress distribution along the cable path in conjunction with the structural deformation includes: Based on the internal stress distribution of the cable, the stress gradient and stress concentration factor are calculated to determine the crack initiation location; based on the crack initiation location and the structural deformation, the cable path displacement change and dynamic strain rate are calculated to determine the dynamic stress distribution of the cable path.

8. The method for analyzing and assessing building electrical safety risks based on big data according to claim 1, characterized in that, The process of formulating a maintenance plan based on the time of the fault occurrence, determining the risk level of the pipe section by combining the characteristics of the settlement area and the pipe burial depth information, and determining the priority ranking of cable route maintenance based on the crack propagation rate and the degree of sheath surface wear include: The remaining safe time window is calculated based on the time of the fault occurrence, the maintenance execution time limit is determined, and a maintenance plan is generated; the stress growth rate of the pipe section is calculated based on the characteristics of the settlement area and the burial depth information of the pipeline, and the risk level of the pipe section is determined; based on the risk level of the pipe section, the crack propagation rate, and the wear degree of the sheath surface, a comprehensive hazard index is calculated, and the priority ranking of cable route maintenance is determined.

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